Instructions to use chardizard/Pythia410mRE-WILD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use chardizard/Pythia410mRE-WILD with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="chardizard/Pythia410mRE-WILD")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("chardizard/Pythia410mRE-WILD")
model = AutoModelForCausalLM.from_pretrained("chardizard/Pythia410mRE-WILD")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use chardizard/Pythia410mRE-WILD with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "chardizard/Pythia410mRE-WILD"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "chardizard/Pythia410mRE-WILD",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/chardizard/Pythia410mRE-WILD

SGLang

How to use chardizard/Pythia410mRE-WILD with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "chardizard/Pythia410mRE-WILD" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "chardizard/Pythia410mRE-WILD",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "chardizard/Pythia410mRE-WILD" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "chardizard/Pythia410mRE-WILD",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use chardizard/Pythia410mRE-WILD with Docker Model Runner:
```
docker model run hf.co/chardizard/Pythia410mRE-WILD
```

chardizard commited on May 7, 2025

Commit

5a63092

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1 Parent(s): d5e39d9

Update README.md

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@@ -1,7 +1,7 @@
 ---
 base_model: EleutherAI/pythia-410m
 library_name: transformers
-model_name: tmp
 tags:
 - generated_from_trainer
 - trl
@@ -9,7 +9,7 @@ tags:
 licence: license
 ---
-# Model Card for tmp
 This model is a fine-tuned version of [EleutherAI/pythia-410m](https://huggingface.co/EleutherAI/pythia-410m).
 It has been trained using [TRL](https://github.com/huggingface/trl).

 ---
 base_model: EleutherAI/pythia-410m
 library_name: transformers
+model_name: Pythia410mRE-WILD
 tags:
 - generated_from_trainer
 - trl
 licence: license
 ---
+# Model Card for Pythia410mRE-WILD
 This model is a fine-tuned version of [EleutherAI/pythia-410m](https://huggingface.co/EleutherAI/pythia-410m).
 It has been trained using [TRL](https://github.com/huggingface/trl).