text stringlengths 7 371k | source stringlengths 2 152 |
|---|---|
Create an Endpoint
After your first login, you will be directed to the [Endpoint creation page](https://ui.endpoints.huggingface.co/new). As an example, this guide will go through the steps to deploy [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-engli... | huggingface/hf-endpoints-documentation/blob/main/docs/source/guides/create_endpoint.mdx |
Choosing a metric for your task
**So you've trained your model and want to see how well it’s doing on a dataset of your choice. Where do you start?**
There is no “one size fits all” approach to choosing an evaluation metric, but some good guidelines to keep in mind are:
## Categories of metrics
There are 3 high-le... | huggingface/evaluate/blob/main/docs/source/choosing_a_metric.mdx |
主要特点
让我们来介绍一下 Gradio 最受欢迎的一些功能！这里是 Gradio 的主要特点：
1. [添加示例输入](#example-inputs)
2. [传递自定义错误消息](#errors)
3. [添加描述内容](#descriptive-content)
4. [设置旗标](#flagging)
5. [预处理和后处理](#preprocessing-and-postprocessing)
6. [样式化演示](#styling)
7. [排队用户](#queuing)
8. [迭代输出](#iterative-outputs)
9. [进度条](#progress-bars)
10. [批处理函数](#bat... | gradio-app/gradio/blob/main/guides/cn/01_getting-started/02_key-features.md |
!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/transformers/blob/main/docs/source/en/perf_train_tpu_tf.md |
Gradio Demo: blocks_random_slider
```
!pip install -q gradio
```
```
import gradio as gr
def func(slider_1, slider_2):
return slider_1 * 5 + slider_2
with gr.Blocks() as demo:
slider = gr.Slider(minimum=-10.2, maximum=15, label="Random Slider (Static)", randomize=True)
slider_1 = gr.Slider(minimu... | gradio-app/gradio/blob/main/demo/blocks_random_slider/run.ipynb |
Git over SSH
You can access and write data in repositories on huggingface.co using SSH (Secure Shell Protocol). When you connect via SSH, you authenticate using a private key file on your local machine.
Some actions, such as pushing changes, or cloning private repositories, will require you to upload your SSH public... | huggingface/hub-docs/blob/main/docs/hub/security-git-ssh.md |
!---
Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or a... | huggingface/transformers/blob/main/examples/research_projects/layoutlmv3/README.md |
State in Blocks
We covered [State in Interfaces](https://gradio.app/interface-state), this guide takes a look at state in Blocks, which works mostly the same.
## Global State
Global state in Blocks works the same as in Interface. Any variable created outside a function call is a reference shared between all users.
... | gradio-app/gradio/blob/main/guides/03_building-with-blocks/03_state-in-blocks.md |
如何使用地图组件绘制图表
Related spaces:
Tags: PLOTS, MAPS
## 简介
本指南介绍如何使用 Gradio 的 `Plot` 组件在地图上绘制地理数据。Gradio 的 `Plot` 组件可以与 Matplotlib、Bokeh 和 Plotly 一起使用。在本指南中，我们将使用 Plotly 进行操作。Plotly 可以让开发人员轻松创建各种地图来展示他们的地理数据。点击[这里](https://plotly.com/python/maps/)查看一些示例。
## 概述
我们将使用纽约市的 Airbnb 数据集，该数据集托管在 kaggle 上，点击[这里](https://www.ka... | gradio-app/gradio/blob/main/guides/cn/05_tabular-data-science-and-plots/plot-component-for-maps.md |
SE-ResNet
**SE ResNet** is a variant of a [ResNet](https://www.paperswithcode.com/method/resnet) that employs [squeeze-and-excitation blocks](https://paperswithcode.com/method/squeeze-and-excitation-block) to enable the network to perform dynamic channel-wise feature recalibration.
## How do I use this model on an i... | huggingface/pytorch-image-models/blob/main/hfdocs/source/models/se-resnet.mdx |
--
title: poseval
emoji: 🤗
colorFrom: blue
colorTo: red
sdk: gradio
sdk_version: 3.19.1
app_file: app.py
pinned: false
tags:
- evaluate
- metric
description: >-
The poseval metric can be used to evaluate POS taggers. Since seqeval does not work well with POS data
that is not in IOB format the poseval is an alter... | huggingface/evaluate/blob/main/metrics/poseval/README.md |
--
title: "Large Language Models: A New Moore's Law?"
thumbnail: /blog/assets/33_large_language_models/01_model_size.jpg
authors:
- user: juliensimon
---
# Large Language Models: A New Moore's Law?
A few days ago, Microsoft and NVIDIA [introduced](https://www.microsoft.com/en-us/research/blog/using-deepspeed-and-me... | huggingface/blog/blob/main/large-language-models.md |
!--Copyright 2021 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/transformers/blob/main/docs/source/en/model_doc/vision-text-dual-encoder.md |
hat is dynamic padding? In the "Batching Inputs together" video, we have seen that to be able to group inputs of different lengths in the same batch, we need to add padding tokens to all the short inputs until they are all of the same length. Here for instance, the longest sentence is the third one, and we need to add ... | huggingface/course/blob/main/subtitles/en/raw/chapter3/02d_dynamic-padding.md |
!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to ... | huggingface/diffusers/blob/main/docs/source/en/api/pipelines/kandinsky3.md |
Datasets server - worker
> Workers that pre-compute and cache the response to /splits, /first-rows, /parquet, /info and /size.
## Configuration
Use environment variables to configure the workers. The prefix of each environment variable gives its scope.
### Uvicorn
The following environment variables are used to c... | huggingface/datasets-server/blob/main/services/worker/README.md |
Differences between Dataset and IterableDataset
There are two types of dataset objects, a [`Dataset`] and an [`IterableDataset`].
Whichever type of dataset you choose to use or create depends on the size of the dataset.
In general, an [`IterableDataset`] is ideal for big datasets (think hundreds of GBs!) due to its l... | huggingface/datasets/blob/main/docs/source/about_mapstyle_vs_iterable.mdx |
Q-Learning Recap [[q-learning-recap]]
*Q-Learning* **is the RL algorithm that** :
- Trains a *Q-function*, an **action-value function** encoded, in internal memory, by a *Q-table* **containing all the state-action pair values.**
- Given a state and action, our Q-function **will search its Q-table for the correspon... | huggingface/deep-rl-class/blob/main/units/en/unit2/q-learning-recap.mdx |
!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/transformers/blob/main/docs/source/en/tasks/zero_shot_object_detection.md |
Quiz
The best way to learn and [to avoid the illusion of competence](https://www.coursera.org/lecture/learning-how-to-learn/illusions-of-competence-BuFzf) **is to test yourself.** This will help you to find **where you need to reinforce your knowledge**.
### Q1: Which of the following interpretations of bias-varian... | huggingface/deep-rl-class/blob/main/units/en/unit6/quiz.mdx |
Access and read Logs
Hugging Face Endpoints provides access to the logs of your Endpoints through the UI in the “Logs” tab of your Endpoint.
You will have access to the build logs of your Image artifacts as well as access to the Container Logs during inference.
<img src="https://raw.githubusercontent.com/huggingfa... | huggingface/hf-endpoints-documentation/blob/main/docs/source/guides/logs.mdx |
Gradio Demo: examples_component
```
!pip install -q gradio
```
```
# Downloading files from the demo repo
import os
os.mkdir('images')
!wget -q -O images/cheetah1.jpg https://github.com/gradio-app/gradio/raw/main/demo/examples_component/images/cheetah1.jpg
!wget -q -O images/lion.jpg https://github.com/gradio-app... | gradio-app/gradio/blob/main/demo/examples_component/run.ipynb |
Additional Readings
These are **optional readings** if you want to go deeper.
## Introduction to Policy Optimization
- [Part 3: Intro to Policy Optimization - Spinning Up documentation](https://spinningup.openai.com/en/latest/spinningup/rl_intro3.html)
## Policy Gradient
- [https://johnwlambert.github.io/policy... | huggingface/deep-rl-class/blob/main/units/en/unit4/additional-readings.mdx |
!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/optimum/blob/main/docs/source/onnxruntime/package_reference/quantization.mdx |
Gradio Demo: number_component
```
!pip install -q gradio
```
```
import gradio as gr
with gr.Blocks() as demo:
gr.Number()
demo.launch()
```
| gradio-app/gradio/blob/main/demo/number_component/run.ipynb |
Gradio Demo: map_airbnb
### Display an interactive map of AirBnB locations with Plotly. Data is hosted on HuggingFace Datasets.
```
!pip install -q gradio plotly
```
```
import gradio as gr
import plotly.graph_objects as go
from datasets import load_dataset
dataset = load_dataset("gradio/NYC-Airbnb-Open... | gradio-app/gradio/blob/main/demo/map_airbnb/run.ipynb |
Res2Net
**Res2Net** is an image model that employs a variation on bottleneck residual blocks, [Res2Net Blocks](https://paperswithcode.com/method/res2net-block). The motivation is to be able to represent features at multiple scales. This is achieved through a novel building block for CNNs that constructs hierarchical ... | huggingface/pytorch-image-models/blob/main/hfdocs/source/models/res2net.mdx |
ow to slice and dice a dataset. Most of the time, the data you work with won’t be perfectly prepared for training models. In this video we’ll explore various features that Datasets provides to clean up your datasets. The Datasets library provides several built-in methods that allow you to wrangle your data. In this vid... | huggingface/course/blob/main/subtitles/en/raw/chapter5/03a_slice-and-dice.md |
Gradio Demo: question-answering
```
!pip install -q gradio torch transformers
```
```
import gradio as gr
from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
model_name = "deepset/roberta-base-squad2"
nlp = pipeline("question-answering", model=model_name, tokenizer=model_name)
conte... | gradio-app/gradio/blob/main/demo/question-answering/run.ipynb |
!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/diffusers/blob/main/docs/source/en/api/loaders/ip_adapter.md |
!--⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
rendered properly in your Markdown viewer.
-->
# Configuration
[`PeftConfigMixin`] is the base configuration class for storing the adapter configuration of a [`PeftModel`], and [`PromptLearningCon... | huggingface/peft/blob/main/docs/source/package_reference/config.md |
!---
Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or a... | huggingface/transformers/blob/main/README_ru.md |
!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/transformers/blob/main/docs/source/en/model_sharing.md |
!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/diffusers/blob/main/docs/source/en/training/lora.md |
--
title: MAPE
emoji: 🤗
colorFrom: blue
colorTo: red
sdk: gradio
sdk_version: 3.19.1
app_file: app.py
pinned: false
tags:
- evaluate
- metric
description: >-
Mean Absolute Percentage Error (MAPE) is the mean percentage error difference between the predicted and actual
values.
---
# Metric Card for MAPE
## Metr... | huggingface/evaluate/blob/main/metrics/mape/README.md |
# Ensemble Adversarial Inception ResNet v2
**Inception-ResNet-v2** is a convolutional neural architecture that builds on the Inception family of architectures but incorporates [residual connections](https://paperswithcode.com/method/residual-connection) (replacing the filter concatenation stage of the Inception archi... | huggingface/pytorch-image-models/blob/main/docs/models/ensemble-adversarial.md |
Using Flair at Hugging Face
[Flair](https://github.com/flairNLP/flair) is a very simple framework for state-of-the-art NLP.
Developed by [Humboldt University of Berlin](https://www.informatik.hu-berlin.de/en/forschung-en/gebiete/ml-en/) and friends.
## Exploring Flair in the Hub
You can find `flair` models by filte... | huggingface/hub-docs/blob/main/docs/hub/flair.md |
`@gradio/button`
```html
<script>
import { Button } from "@gradio/button";
</script>
<button type="primary|secondary" href="string" on:click="{e.detail === href}">
content
</button>
```
| gradio-app/gradio/blob/main/js/accordion/README.md |
he Hugging Face Datasets library: A Quick overview. The Hugging Face Datasets library is a library that provides an API to quickly download many public datasets and preprocess them. In this video we will explore how to do that. The downloading part is easy: with the load_dataset function, you can directly download and ... | huggingface/course/blob/main/subtitles/en/raw/chapter3/02a_datasets-overview-pt.md |
--
title: "Why we’re switching to Hugging Face Inference Endpoints, and maybe you should too"
thumbnail: /blog/assets/78_ml_director_insights/mantis1.png
authors:
- user: mattupson
guest: true
---
# Why we’re switching to Hugging Face Inference Endpoints, and maybe you should too
Hugging Face recently launched [I... | huggingface/blog/blob/main/mantis-case-study.md |
--
title: ROUGE
emoji: 🤗
colorFrom: blue
colorTo: red
sdk: gradio
sdk_version: 3.19.1
app_file: app.py
pinned: false
tags:
- evaluate
- metric
description: >-
ROUGE, or Recall-Oriented Understudy for Gisting Evaluation, is a set of metrics and a software package used for
evaluating automatic summarization and mac... | huggingface/evaluate/blob/main/metrics/rouge/README.md |
!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/diffusers/blob/main/docs/source/en/api/pipelines/audioldm.md |
efore diving in character-based tokenization, understanding why this kind of tokenization is interesting requires understanding the flaws of word-based tokenization. If you haven't seen the first video on word-based tokenization we recommend you check it out before looking at this video. Let's take a look at character-... | huggingface/course/blob/main/subtitles/en/raw/chapter2/04c_character-based-tokenizers.md |
Hands-on
Now that you learned the basics of multi-agents, you're ready to train your first agents in a multi-agent system: **a 2vs2 soccer team that needs to beat the opponent team**.
And you’re going to participate in AI vs. AI challenges where your trained agent will compete against other classmates’ **agents ever... | huggingface/deep-rl-class/blob/main/units/en/unit7/hands-on.mdx |
Gradio Demo: sales_projections
```
!pip install -q gradio pandas numpy matplotlib
```
```
import matplotlib.pyplot as plt
import numpy as np
import gradio as gr
def sales_projections(employee_data):
sales_data = employee_data.iloc[:, 1:4].astype("int").to_numpy()
regression_values = np.apply_along_axis(... | gradio-app/gradio/blob/main/demo/sales_projections/run.ipynb |
Metric Card for F1
## Metric Description
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
## How to Use
At minimum, this metric requires predictions and references as input
```python
>>> f1_metric = datasets... | huggingface/datasets/blob/main/metrics/f1/README.md |
!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/transformers/blob/main/docs/source/en/model_doc/timesformer.md |
!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/transformers/blob/main/docs/source/en/model_doc/swinv2.md |
!--Copyright 2020 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/transformers/blob/main/docs/source/en/model_doc/rembert.md |
!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/diffusers/blob/main/docs/source/en/using-diffusers/inference_with_lcm_lora.md |
Latent Consistency Distillation Example:
[Latent Consistency Models (LCMs)](https://arxiv.org/abs/2310.04378) is a method to distill a latent diffusion model to enable swift inference with minimal steps. This example demonstrates how to use latent consistency distillation to distill SDXL for inference with few timest... | huggingface/diffusers/blob/main/examples/consistency_distillation/README_sdxl.md |
!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/transformers/blob/main/docs/source/en/model_doc/autoformer.md |
--
title: "DuckDB: analyze 50,000+ datasets stored on the Hugging Face Hub"
thumbnail: /blog/assets/hub_duckdb/hub_duckdb.png
authors:
- user: stevhliu
- user: lhoestq
- user: severo
---
# DuckDB: run SQL queries on 50,000+ datasets on the Hugging Face Hub
The Hugging Face Hub is dedicated to providing open access ... | huggingface/blog/blob/main/hub-duckdb.md |
Gradio and W&B Integration
Related spaces: https://huggingface.co/spaces/akhaliq/JoJoGAN
Tags: WANDB, SPACES
Contributed by Gradio team
## Introduction
In this Guide, we'll walk you through:
- Introduction of Gradio, and Hugging Face Spaces, and Wandb
- How to setup a Gradio demo using the Wandb integration for Jo... | gradio-app/gradio/blob/main/guides/06_integrating-other-frameworks/Gradio-and-Wandb-Integration.md |
Gradio Demo: duplicatebutton_component
```
!pip install -q gradio
```
```
import gradio as gr
with gr.Blocks() as demo:
gr.DuplicateButton()
demo.launch()
```
| gradio-app/gradio/blob/main/demo/duplicatebutton_component/run.ipynb |
Widget Examples
Note that each widget example can also optionally describe the corresponding model output, directly in the `output` property. See [the spec](./models-widgets#example-outputs) for more details.
## Natural Language Processing
### Fill-Mask
```yaml
widget:
- text: "Paris is the <mask> of France."
ex... | huggingface/hub-docs/blob/main/docs/hub/models-widgets-examples.md |
!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/diffusers/blob/main/docs/source/en/api/models/unet.md |
--
title: "Building an AI WebTV"
thumbnail: /blog/assets/156_ai_webtv/thumbnail.gif
authors:
- user: jbilcke-hf
---
# Building an AI WebTV
The AI WebTV is an experimental demo to showcase the latest advancements in automatic video and music synthesis.
👉 Watch the stream now by going to the [AI WebTV Space](https:/... | huggingface/blog/blob/main/ai-webtv.md |
Stable Diffusion
## Overview
Stable Diffusion was proposed in [Stable Diffusion Announcement](https://stability.ai/blog/stable-diffusion-announcement) by Patrick Esser and Robin Rombach and the Stability AI team.
The summary of the model is the following:
*Stable Diffusion is a text-to-image model that will empowe... | huggingface/diffusers/blob/main/src/diffusers/pipelines/stable_diffusion/README.md |
p align="center">
<br/>
<img alt="huggingface_hub library logo" src="https://huggingface.co/datasets/huggingface/documentation-images/raw/main/huggingface_hub.svg" width="376" height="59" style="max-width: 100%;">
<br/>
</p>
<p align="center">
<i>Huggingface Hub के लिए आधिकारिक पायथन क्लाइंट।</i>
</p>
<p ... | huggingface/huggingface_hub/blob/main/README_hi.md |
!--Copyright 2020 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/transformers/blob/main/docs/source/en/model_doc/lxmert.md |
The tokenization pipeline
When calling `Tokenizer.encode` or
`Tokenizer.encode_batch`, the input
text(s) go through the following pipeline:
- `normalization`
- `pre-tokenization`
- `model`
- `post-processing`
We'll see in details what happens during each of those steps in detail,
as well as when you want to... | huggingface/tokenizers/blob/main/docs/source-doc-builder/pipeline.mdx |
TResNet
A **TResNet** is a variant on a [ResNet](https://paperswithcode.com/method/resnet) that aim to boost accuracy while maintaining GPU training and inference efficiency. They contain several design tricks including a SpaceToDepth stem, [Anti-Alias downsampling](https://paperswithcode.com/method/anti-alias-downs... | huggingface/pytorch-image-models/blob/main/docs/models/tresnet.md |
Configure the Dataset Viewer
The Dataset Viewer supports many [data files formats](./datasets-adding#file-formats), from text to tabular and from image to audio formats.
It also separates the train/validation/test splits based on file and folder names.
To configure the Dataset Viewer for your dataset, first make sur... | huggingface/hub-docs/blob/main/docs/hub/datasets-viewer-configure.md |
Author: [@vasudevgupta7](https://github.com/thevasudevgupta/)
## Intro
In this project, we fine-tuned [**BigBird**](https://arxiv.org/abs/2007.14062) on [**natural-questions**](https://huggingface.co/datasets/natural_questions) dataset for **question-answering** task on long documents. **BigBird**, is a **sparse-atte... | huggingface/transformers/blob/main/examples/research_projects/jax-projects/big_bird/README.md |
--
title: Fine tuning CLIP with Remote Sensing (Satellite) images and captions
thumbnail: /blog/assets/30_clip_rsicd/clip_schematic.png
authors:
- user: arampacha
guest: true
- user: devv
guest: true
- user: goutham794
guest: true
- user: cataluna84
guest: true
- user: ghosh-r
guest: true
- user: sujitpal
g... | huggingface/blog/blob/main/fine-tune-clip-rsicd.md |
!---
Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or a... | huggingface/transformers/blob/main/notebooks/README.md |
--
title: "Multivariate Probabilistic Time Series Forecasting with Informer"
thumbnail: /blog/assets/134_informer/thumbnail.png
authors:
- user: elisim
guest: true
- user: nielsr
- user: kashif
---
# Multivariate Probabilistic Time Series Forecasting with Informer
<script async defer src="https://unpkg.com/medium... | huggingface/blog/blob/main/informer.md |
SE-ResNet
**SE ResNet** is a variant of a [ResNet](https://www.paperswithcode.com/method/resnet) that employs [squeeze-and-excitation blocks](https://paperswithcode.com/method/squeeze-and-excitation-block) to enable the network to perform dynamic channel-wise feature recalibration.
## How do I use this model on an i... | huggingface/pytorch-image-models/blob/main/docs/models/se-resnet.md |
!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to ... | huggingface/diffusers/blob/main/docs/source/en/api/pipelines/kandinsky_v22.md |
--
title: "Huggy Lingo: Using Machine Learning to Improve Language Metadata on the Hugging Face Hub"
thumbnail: blog/assets/156_huggylingo/Huggy_Lingo.png
authors:
- user: davanstrien
---
## Huggy Lingo: Using Machine Learning to Improve Language Metadata on the Hugging Face Hub
**tl;dr**: We're using machine learn... | huggingface/blog/blob/main/huggy-lingo.md |
!--Copyright 2020 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/transformers/blob/main/docs/source/en/main_classes/trainer.md |
Gradio Demo: upload_button_component_events
```
!pip install -q gradio
```
```
import gradio as gr
with gr.Blocks() as demo:
with gr.Row():
with gr.Column():
upload_btn = gr.UploadButton(label="Upload Single File", file_count="single")
with gr.Column():
output_fil... | gradio-app/gradio/blob/main/demo/upload_button_component_events/run.ipynb |
Normalization and pre-tokenization[[normalization-and-pre-tokenization]]
<CourseFloatingBanner chapter={6}
classNames="absolute z-10 right-0 top-0"
notebooks={[
{label: "Google Colab", value: "https://colab.research.google.com/github/huggingface/notebooks/blob/master/course/en/chapter6/section4.ipynb"},
{... | huggingface/course/blob/main/chapters/en/chapter6/4.mdx |
!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/simulate/blob/main/docs/source/howto/map_pools.mdx |
@gradio/imageeditor
## 0.2.0
### Features
- [#6809](https://github.com/gradio-app/gradio/pull/6809) [`1401d99`](https://github.com/gradio-app/gradio/commit/1401d99ade46d87da75b5f5808a3354c49f1d1ea) - Fix `ImageEditor` interaction story. Thanks [@hannahblair](https://github.com/hannahblair)!
## 0.1.5
### Fixes
-... | gradio-app/gradio/blob/main/js/imageeditor/CHANGELOG.md |
How to contribute to simulate?
[](CODE_OF_CONDUCT.md)
Simulation environments is an open source project, so all contributions and suggestions are welcome.
You can contribute in many different ways: giving ideas, answering ques... | huggingface/simulate/blob/main/CONTRIBUTING.md |
Gradio Demo: chatinterface_system_prompt
```
!pip install -q gradio
```
```
import gradio as gr
import time
def echo(message, history, system_prompt, tokens):
response = f"System prompt: {system_prompt}\n Message: {message}."
for i in range(min(len(response), int(tokens))):
time.sleep(0.05)
... | gradio-app/gradio/blob/main/demo/chatinterface_system_prompt/run.ipynb |
CSP-ResNeXt
**CSPResNeXt** is a convolutional neural network where we apply the Cross Stage Partial Network (CSPNet) approach to [ResNeXt](https://paperswithcode.com/method/resnext). The CSPNet partitions the feature map of the base layer into two parts and then merges them through a cross-stage hierarchy. The use of... | huggingface/pytorch-image-models/blob/main/hfdocs/source/models/csp-resnext.mdx |
!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/diffusers/blob/main/docs/source/en/api/pipelines/panorama.md |
!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/simulate/blob/main/docs/source/api/actors.mdx |
ow to preprocess pairs of sentences? We have seen how to tokenize single sentences and batch them together in the "Batching inputs together" video. If this code look unfamiliar to you, be sure to check that video again! Here we will focus on tasks that classify pairs of sentences. For instance, we may want to classify ... | huggingface/course/blob/main/subtitles/en/raw/chapter3/02c_preprocess-sentence-pairs-pt.md |
!--⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
rendered properly in your Markdown viewer.
-->
# Download files from the Hub
The `huggingface_hub` library provides functions to download files from the repositories
stored on the Hub. You can use... | huggingface/huggingface_hub/blob/main/docs/source/en/guides/download.md |
Two types of value-based methods [[two-types-value-based-methods]]
In value-based methods, **we learn a value function** that **maps a state to the expected value of being at that state.**
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit3/vbm-1.jpg" alt="Value B... | huggingface/deep-rl-class/blob/main/units/en/unit2/two-types-value-based-methods.mdx |
The Hugging Face Course
This repo contains the content that's used to create the **[Hugging Face course](https://huggingface.co/course/chapter1/1)**. The course teaches you about applying Transformers to various tasks in natural language processing and beyond. Along the way, you'll learn how to use the [Hugging Face]... | huggingface/course/blob/main/README.md |
The advantages and disadvantages of policy-gradient methods
At this point, you might ask, "but Deep Q-Learning is excellent! Why use policy-gradient methods?". To answer this question, let's study the **advantages and disadvantages of policy-gradient methods**.
## Advantages
There are multiple advantages over value... | huggingface/deep-rl-class/blob/main/units/en/unit4/advantages-disadvantages.mdx |
!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to ... | huggingface/diffusers/blob/main/docs/source/en/api/pipelines/shap_e.md |
Gradio Demo: streaming_wav2vec
```
!pip install -q gradio torch transformers
```
```
from transformers import pipeline
import gradio as gr
import time
p = pipeline("automatic-speech-recognition")
def transcribe(audio, state=""):
time.sleep(2)
text = p(audio)["text"]
state += text + " "
return st... | gradio-app/gradio/blob/main/demo/streaming_wav2vec/run.ipynb |
Adding a Sign-In with HF button to your Space
You can enable a built-in sign-in flow in your Space by seamlessly creating and associating an [OAuth/OpenID connect](https://developer.okta.com/blog/2019/10/21/illustrated-guide-to-oauth-and-oidc) app so users can log in with their HF account.
This enables new use cases... | huggingface/hub-docs/blob/main/docs/hub/spaces-oauth.md |
!---
Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or ag... | huggingface/diffusers/blob/main/examples/README.md |
Fine-tuning for image classification using LoRA and 🤗 PEFT
## Vision Transformer model from transformers
[](https://colab.research.google.com/github/huggingface/peft/blob/main/examples/image_classification/image_classification_peft_lora.ipynb... | huggingface/peft/blob/main/examples/image_classification/README.md |
--
title: "Generating Human-level Text with Contrastive Search in Transformers 🤗"
thumbnail: /blog/assets/115_introducing_contrastive_search/thumbnail.png
authors:
- user: GMFTBY
---
# Generating Human-level Text with Contrastive Search in Transformers 🤗
****
<a target="_blank" href="https://colab.research.google... | huggingface/blog/blob/main/introducing-csearch.md |
!--Copyright 2023 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/optimum/blob/main/docs/source/exporters/tflite/package_reference/export.mdx |
--
title: "AMD + 🤗: Large Language Models Out-of-the-Box Acceleration with AMD GPU"
thumbnail: /blog/assets/optimum_amd/amd_hf_logo_fixed.png
authors:
- user: fxmarty
- user: IlyasMoutawwakil
- user: mohitsha
- user: echarlaix
- user: seungrokj
guest: true
- user: mfuntowicz
---
# AMD + 🤗: Large Language Models Ou... | huggingface/blog/blob/main/huggingface-and-optimum-amd.md |
RexNet
**Rank Expansion Networks** (ReXNets) follow a set of new design principles for designing bottlenecks in image classification models. Authors refine each layer by 1) expanding the input channel size of the convolution layer and 2) replacing the [ReLU6s](https://www.paperswithcode.com/method/relu6).
## How do ... | huggingface/pytorch-image-models/blob/main/docs/models/rexnet.md |
RegNetY
**RegNetY** is a convolutional network design space with simple, regular models with parameters: depth $d$, initial width $w\_{0} > 0$, and slope $w\_{a} > 0$, and generates a different block width $u\_{j}$ for each block $j < d$. The key restriction for the RegNet types of model is that there is a linear par... | huggingface/pytorch-image-models/blob/main/docs/models/regnety.md |
Feature Extraction
All of the models in `timm` have consistent mechanisms for obtaining various types of features from the model for tasks besides classification.
## Penultimate Layer Features (Pre-Classifier Features)
The features from the penultimate model layer can be obtained in several ways without requiring m... | huggingface/pytorch-image-models/blob/main/docs/feature_extraction.md |
component-styles
## Textbox
| name | type | description |
| ----------- | ------------------------------------ | ------------------------------ |
| `rounded` | `bool` or `(bool, bool, bool, bool)` | corners of text input |
| `border` | `bool` or... | gradio-app/gradio/blob/main/style.md |
!--Copyright 2021 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed ... | huggingface/transformers/blob/main/docs/source/en/model_doc/big_bird.md |
User access tokens
## What are User Access Tokens?
User Access Tokens are the preferred way to authenticate an application or notebook to Hugging Face services. You can manage your access tokens in your [settings](https://huggingface.co/settings/tokens).
<div class="flex justify-center">
<img class="block dark:hidd... | huggingface/hub-docs/blob/main/docs/hub/security-tokens.md |
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