Instructions to use roscazo/WL_DISEASE_NER_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roscazo/WL_DISEASE_NER_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="roscazo/WL_DISEASE_NER_v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("roscazo/WL_DISEASE_NER_v1") model = AutoModelForTokenClassification.from_pretrained("roscazo/WL_DISEASE_NER_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from roscazo/WL_DISEASE_NER_v1: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/roscazo/WL_DISEASE_NER_v1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://roscazo/WL_DISEASE_NER_v1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/roscazo/WL_DISEASE_NER_v1/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- bc8e849a1b213e78627e61789cc44f2edd52a64db3432bc5d407601cbdd3734c
- Size of remote file:
- 496 MB
- SHA256:
- fc11ff2d58053eefe2965f0cec28a9ac7af073b053aff4756458d17965e911dc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.