Instructions to use divers/flan-base-req-extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use divers/flan-base-req-extractor with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("divers/flan-base-req-extractor") model = AutoModelForSeq2SeqLM.from_pretrained("divers/flan-base-req-extractor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from divers/flan-base-req-extractor: direct link, hf CLI and curl.
- Browser
- Download file 990 MB
-
https://huggingface.co/divers/flan-base-req-extractor/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://divers/flan-base-req-extractor/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/divers/flan-base-req-extractor/resolve/main/pytorch_model.bin
990 MB
- Xet hash:
- fc7ccc32ee6f23d8448fd7c60b3d8128a01e462af939937296f96e80494b5b7f
- Size of remote file:
- 990 MB
- SHA256:
- 4091bae88c716973e7ab95940203b06fecf4c89e52554ae7d4c997b549acb29d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.