Instructions to use finding-fossils/metaextractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use finding-fossils/metaextractor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="finding-fossils/metaextractor")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("finding-fossils/metaextractor") model = AutoModelForTokenClassification.from_pretrained("finding-fossils/metaextractor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from finding-fossils/metaextractor: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/finding-fossils/metaextractor/resolve/refs%2Fpr%2F4/pytorch_model.bin
- Command line
-
hf download hf://finding-fossils/metaextractor@refs/pr/4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/finding-fossils/metaextractor/resolve/refs%2Fpr%2F4/pytorch_model.bin
496 MB
- Xet hash:
- 086ee4c96a09bc570e0d4018d00fc745e214fe349936c8ec6c52fff9d411cf70
- Size of remote file:
- 496 MB
- SHA256:
- 58e6d0c505cadb3389a805ec9b08e579725be60ea75b3f73f899f289832fb437
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.