Instructions to use learn2pro/buddygpt-0.1b-chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use learn2pro/buddygpt-0.1b-chat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="learn2pro/buddygpt-0.1b-chat") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("learn2pro/buddygpt-0.1b-chat", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use learn2pro/buddygpt-0.1b-chat with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "learn2pro/buddygpt-0.1b-chat" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "learn2pro/buddygpt-0.1b-chat", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/learn2pro/buddygpt-0.1b-chat
- SGLang
How to use learn2pro/buddygpt-0.1b-chat 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 "learn2pro/buddygpt-0.1b-chat" \ --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": "learn2pro/buddygpt-0.1b-chat", "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 "learn2pro/buddygpt-0.1b-chat" \ --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": "learn2pro/buddygpt-0.1b-chat", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use learn2pro/buddygpt-0.1b-chat with Docker Model Runner:
docker model run hf.co/learn2pro/buddygpt-0.1b-chat
- Xet hash:
- d140a91e3f70cd4410bc8fcbd78b791b086e10182b973cf6d12c2d302fededbc
- Size of remote file:
- 5.69 kB
- SHA256:
- 466f0437d44f256d1dc05e7947ef0480fc85a028ac1d19fb38f5844994ac6f4b
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