Instructions to use ryefoxlime/TADBot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ryefoxlime/TADBot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ryefoxlime/TADBot")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ryefoxlime/TADBot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ryefoxlime/TADBot with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ryefoxlime/TADBot" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ryefoxlime/TADBot", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ryefoxlime/TADBot
- SGLang
How to use ryefoxlime/TADBot 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 "ryefoxlime/TADBot" \ --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": "ryefoxlime/TADBot", "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 "ryefoxlime/TADBot" \ --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": "ryefoxlime/TADBot", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ryefoxlime/TADBot with Docker Model Runner:
docker model run hf.co/ryefoxlime/TADBot
| [project] | |
| name = "TADBot" | |
| version = "0.1.0" | |
| description = "Add your description here" | |
| readme = "README.md" | |
| requires-python = ">=3.12" | |
| dependencies = [ | |
| "torch>=2.5.1", | |
| "torchaudio>=2.5.1", | |
| "torchvision>=0.20.1", | |
| "deepface>=0.0.93", | |
| "timm>=1.0.11", | |
| "thop>=0.1.1.post2209072238", | |
| "scikit-learn>=1.5.2", | |
| "matplotlib>=3.9.2", | |
| "torchsampler>=0.1.2", | |
| "tf-keras>=2.18.0", | |
| "pyaudio>=0.2.14", | |
| "pyttsx3>=2.98", | |
| "ollama>=0.3.3", | |
| "chromadb>=0.5.20", | |
| "speechrecognition>=3.11.0", | |
| ] | |
| deepface = {git = "https://github.com/serengil/deepface", tag="v0.0.93"} | |