Instructions to use vamsipamidi/BART_ToS_mixed_sampling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vamsipamidi/BART_ToS_mixed_sampling with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("vamsipamidi/BART_ToS_mixed_sampling") model = AutoModelForSeq2SeqLM.from_pretrained("vamsipamidi/BART_ToS_mixed_sampling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from vamsipamidi/BART_ToS_mixed_sampling: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/vamsipamidi/BART_ToS_mixed_sampling/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://vamsipamidi/BART_ToS_mixed_sampling/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/vamsipamidi/BART_ToS_mixed_sampling/resolve/main/pytorch_model.bin
242 MB
- Xet hash:
- e0ffbb12daa4387ea4895ea7ded77dc9c796ce9dd26ca14dfe38ce3e4ee9f714
- Size of remote file:
- 242 MB
- SHA256:
- 26bac4e81532837734c475c55a860aae26d8c28a7c0a5310479bfbee7c6dd185
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