Instructions to use ethzanalytics/ai-msgbot-gpt2-M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ethzanalytics/ai-msgbot-gpt2-M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ethzanalytics/ai-msgbot-gpt2-M")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ethzanalytics/ai-msgbot-gpt2-M") model = AutoModelForCausalLM.from_pretrained("ethzanalytics/ai-msgbot-gpt2-M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ethzanalytics/ai-msgbot-gpt2-M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ethzanalytics/ai-msgbot-gpt2-M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ethzanalytics/ai-msgbot-gpt2-M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ethzanalytics/ai-msgbot-gpt2-M
- SGLang
How to use ethzanalytics/ai-msgbot-gpt2-M 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 "ethzanalytics/ai-msgbot-gpt2-M" \ --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": "ethzanalytics/ai-msgbot-gpt2-M", "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 "ethzanalytics/ai-msgbot-gpt2-M" \ --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": "ethzanalytics/ai-msgbot-gpt2-M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ethzanalytics/ai-msgbot-gpt2-M with Docker Model Runner:
docker model run hf.co/ethzanalytics/ai-msgbot-gpt2-M
Commit History
-
Adding `safetensors` variant of this model (#1)
Verified signature- Adding `safetensors` variant of this model (5b097d7d61e26083223711ac42691d1456ddd784) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>db19c50
-
Update README.md
6351371 -
Update README.md
33353d8 -
:memo: update citations
890a446 -
Update README.md
598fcde
-
Update README.md
35597ec -
Update README.md
572f80e
-
Update README.md
d7bd96f
-
Update README.md
965f757 -
Create README.md
b7327a1 -
Update from $USER
peter szemraj68a98ef -
initial commit
929a274