Instructions to use medspaner/roberta-es-clinical-trials-neg-spec-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use medspaner/roberta-es-clinical-trials-neg-spec-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="medspaner/roberta-es-clinical-trials-neg-spec-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("medspaner/roberta-es-clinical-trials-neg-spec-ner") model = AutoModelForTokenClassification.from_pretrained("medspaner/roberta-es-clinical-trials-neg-spec-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from medspaner/roberta-es-clinical-trials-neg-spec-ner: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/medspaner/roberta-es-clinical-trials-neg-spec-ner/resolve/67316fe01edae94ac8f3f64746cd99c5e6008c91/pytorch_model.bin
- Command line
-
hf download hf://medspaner/roberta-es-clinical-trials-neg-spec-ner@67316fe01edae94ac8f3f64746cd99c5e6008c91/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/medspaner/roberta-es-clinical-trials-neg-spec-ner/resolve/67316fe01edae94ac8f3f64746cd99c5e6008c91/pytorch_model.bin
496 MB
- Xet hash:
- 32cb58126c138986e836e055d99d7e636888a7f31cccd9e4d23bbca1bd86de25
- Size of remote file:
- 496 MB
- SHA256:
- 56f0b56e479da404bb45ad178b780726c2a13b4760c3fa5d883df460ef3216cc
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