Instructions to use DhaneshV/T2FPipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DhaneshV/T2FPipeline with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("DhaneshV/T2FPipeline") model = AutoModelForSeq2SeqLM.from_pretrained("DhaneshV/T2FPipeline", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (d0cb6229fd104db24ee9363e171dbf1303e42291) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>584efe3
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Update testing.py
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Update testing.py
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Adding `safetensors` variant of this model (#2)
- Adding `safetensors` variant of this model (5047a5a360486a7c4732fae7ca308daf204ca24b) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>7f561eb -
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commit files to HF hub
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initial commit
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