Instructions to use keonju/chat_bot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keonju/chat_bot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="keonju/chat_bot")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("keonju/chat_bot") model = AutoModelForCausalLM.from_pretrained("keonju/chat_bot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use keonju/chat_bot with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "keonju/chat_bot" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "keonju/chat_bot", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/keonju/chat_bot
- SGLang
How to use keonju/chat_bot 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 "keonju/chat_bot" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "keonju/chat_bot", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "keonju/chat_bot" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "keonju/chat_bot", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use keonju/chat_bot with Docker Model Runner:
docker model run hf.co/keonju/chat_bot
Download pytorch_model.bin from keonju/chat_bot: direct link, hf CLI and curl.
- Browser
- Download file 513 MB
-
https://huggingface.co/keonju/chat_bot/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://keonju/chat_bot/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/keonju/chat_bot/resolve/main/pytorch_model.bin
513 MB
- Xet hash:
- 896e3053ccb2be7005375d07c70ccedec0795c624497b71eaf1d0872ad22ca89
- Size of remote file:
- 513 MB
- SHA256:
- d8d9ee7bfd6ddbfc63c0bad4d64f2ea88706fc435ee6827ad4b48d791e5692aa
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