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")# pip install -U transformers accelerate # 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
Commit History
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Final Version of the Project
51ef5ad
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Raspberry pi codes
6e9c870 -
Upload TAD.py (#1)
Verified signature- Upload TAD.py (2ebbddda40372666ed324a9dbb374b84d6ec87f7) Co-authored-by: Tharrun S <TheDunkinNinja@users.noreply.huggingface.co>2dd581a -
updated Readme file
8143c42
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Update README.md
Verified signature19d9abc -
Update README.md
Verified signature4640be7 -
Updated Readme with information about TTS and SST
0f13af6
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tidied up the code
3d5069a -
Full Fine Tuned Model
d1734fa -
Fine tuned model
313f14f -
Updated Hyperparams and dataset
dbebf53 -
Model Finetune Params and dependencies
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Fine Tuned v0.0.1
3301578 -
added lib for finetuning
b37902d -
updated gitignore to ignore model tensors
06436d4 -
updated the python project version
8eb51e6
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fixed error
7cf8e9f -
updating gitignore with checkpoint file
2c0e56e -
FER Working on RPi with ~30sec predict time
a583b5e -
minor changes
54cac64
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Updated README with Information about the FER Model
072ee0e -
importing only certain func from main
8e0d21f -
FER alpha 0.1
499f0dc -
removed __pycache__ files and added them to .gitignore
49cca10 -
updated face recognition; added support for ipykernel and ipywidgets; included .gitignore
8cc5e9d -
added basic files and updated env
9de35b0
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updated readme and required libs
dca99f4 -
addeed huggingface_hub
892da85 -
Configured to use python 3.11 as default
26b98fd -
Restructured the project files
0e084be
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Upload 26 files
Verified signatureTAD Bot Face Detection algorithm18a9dce -
initial commit
Verified signaturede8e1d2