Instructions to use bhsu/my_awesome_eli5_clm-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use bhsu/my_awesome_eli5_clm-model with Transformers:

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

pipe = pipeline("text-generation", model="bhsu/my_awesome_eli5_clm-model")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("bhsu/my_awesome_eli5_clm-model")
model = AutoModelForCausalLM.from_pretrained("bhsu/my_awesome_eli5_clm-model", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use bhsu/my_awesome_eli5_clm-model with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "bhsu/my_awesome_eli5_clm-model"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "bhsu/my_awesome_eli5_clm-model",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/bhsu/my_awesome_eli5_clm-model

SGLang

How to use bhsu/my_awesome_eli5_clm-model 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 "bhsu/my_awesome_eli5_clm-model" \
    --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": "bhsu/my_awesome_eli5_clm-model",
		"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 "bhsu/my_awesome_eli5_clm-model" \
        --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": "bhsu/my_awesome_eli5_clm-model",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use bhsu/my_awesome_eli5_clm-model with Docker Model Runner:
```
docker model run hf.co/bhsu/my_awesome_eli5_clm-model
```

my_awesome_eli5_clm-model / pytorch_model.bin

Commit History

End of training

cbce765

Brian Hsu commited on Jul 6, 2023

Training in progress, step 3000

b808d2c

Brian Hsu commited on Jul 6, 2023

Training in progress, step 2500

f415d93

Brian Hsu commited on Jul 6, 2023

Training in progress, step 1500

e2a2f38

Brian Hsu commited on Jul 6, 2023

Training in progress, step 500

5363f08

Brian Hsu commited on Jul 6, 2023

Commit History

End of training cbce765

Training in progress, step 3000 b808d2c

Training in progress, step 2500 f415d93

Training in progress, step 1500 e2a2f38

Training in progress, step 500 5363f08

End of training

cbce765

Training in progress, step 3000

b808d2c

Training in progress, step 2500

f415d93

Training in progress, step 1500

e2a2f38

Training in progress, step 500

5363f08