Update README.md

README.md

@@ -1,151 +1,5 @@
-<<<<<<< HEAD
 ---
-license: gemma
-base_model: google/gemma-7b
-tags:
-- alignment-handbook
-- trl
-- sft
-- generated_from_trainer
-- trl
-- sft
-- generated_from_trainer
-datasets:
-- masakhane/african-translated-alpaca
-model-index:
-- name: zephyr-7b-gemma-sft-african-alpaca
-  results: []
 language:
-- af
-- am
 - ar
-- en
-- ee
----
-
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
-# zephyr-7b-gemma-sft-alpaca
-
-This model is a fine-tuned version of [google/gemma-7b](https://huggingface.co/google/gemma-7b) on the masakhane/african-translated-alpaca dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.2737
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 1e-05
-- train_batch_size: 1
-- eval_batch_size: 1
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 8
-- gradient_accumulation_steps: 2
-- total_train_batch_size: 16
-- total_eval_batch_size: 8
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 3
-
-### Training results
-
-| Training Loss | Epoch | Step  | Validation Loss |
-|:-------------:|:-----:|:-----:|:---------------:|
-| 0.8671        | 1.0   | 5882  | 0.7445          |
-| 0.5235        | 2.0   | 11764 | 0.3905          |
-| 0.3309        | 3.0   | 17646 | 0.2737          |
-
-
-### Framework versions
-
-- Transformers 4.39.0.dev0
-- Pytorch 2.2.1+cu121
-- Datasets 2.14.6
-- Tokenizers 0.15.2
-
-
-
-
-### Usage
-
-```python
-
-# Install transformers from source - only needed for versions <= v4.34
-# pip install git+https://github.com/huggingface/transformers.git
-# pip install accelerate
-
-import torch
-from transformers import pipeline
-
-pipe = pipeline("text-generation", model="masakhane/zephyr-7b-gemma-sft-african-alpaca", torch_dtype=torch.bfloat16, device_map="auto")
-
-# We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
-messages = [
-    {
-        "role": "system",
-        "content": "You are a friendly chatbot who answewrs question in given language",
-    },
-    {"role": "user", "content": "what is the 3 biggest countrys in Africa?"},
-]
-prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
-outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
-print(outputs[0]["generated_text"])
-# <|system|>
-# You are a friendly chatbot who always responds in the style of a pirate<eos>
-# <|user|>
-# what is the 3 biggest countrys in Africa?<eos>
-# <|assistant|>
-# The 3 biggest countries in Africa are Nigeria, Ethiopia and South Africa.
-```
-
-
-### Quantized Versions through bitsandbytes
-
-``` python
-
-import torch
-from transformers import pipeline
-from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
-
-
-quantization_config = BitsAndBytesConfig(load_in_4bit=True)
-
-tokenizer = AutoTokenizer.from_pretrained("masakhane/zephyr-7b-gemma-sft-african-alpaca")
-model = AutoModelForCausalLM.from_pretrained("masakhane/zephyr-7b-gemma-sft-african-alpaca", quantization_config=quantization_config)
-
-
-pipe = pipeline("text-generation", model=model,tokenizer=tokenizer, torch_dtype=torch.bfloat16, device_map="auto")
-
-messages = [
-    {
-        "role": "system",
-        "content": "You are a friendly chatbot who answewrs question in given language",
-    },
-    {"role": "user", "content": "list languages in Africa?"},
-]
-prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
-outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
-print(outputs[0]["generated_text"])
-
-```
-=======
----
-license: apache-2.0
----
->>>>>>> 28411f788e80295e38a461856e2fdd0241da04af
+pipeline_tag: text-generation
+---