Instructions to use tarekziade/Control_Token_Joint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tarekziade/Control_Token_Joint with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("tarekziade/Control_Token_Joint") model = AutoModelForSeq2SeqLM.from_pretrained("tarekziade/Control_Token_Joint", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/encoder_model_quantized.onnx from tarekziade/Control_Token_Joint: direct link, hf CLI and curl.
- Browser
- Download file 82.6 MB
-
https://huggingface.co/tarekziade/Control_Token_Joint/resolve/main/onnx/encoder_model_quantized.onnx
- Command line
-
hf download hf://tarekziade/Control_Token_Joint/onnx/encoder_model_quantized.onnx
-
curl -L -o encoder_model_quantized.onnx https://huggingface.co/tarekziade/Control_Token_Joint/resolve/main/onnx/encoder_model_quantized.onnx
82.6 MB
- Xet hash:
- 866aa17e065420909db1f40385666bb499b6f7aa7750a7d7c7851fe8ba04f639
- Size of remote file:
- 82.6 MB
- SHA256:
- b5b8855fede26ea6e36636ebb23c5a4c0714c98e73af93f2a99a0c837ba6a469
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