Instructions to use samanta-scratch/Roberta-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use samanta-scratch/Roberta-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="samanta-scratch/Roberta-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("samanta-scratch/Roberta-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("samanta-scratch/Roberta-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from samanta-scratch/Roberta-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/samanta-scratch/Roberta-finetuned-ner/resolve/main/training_args.bin
- Command line
-
hf download hf://samanta-scratch/Roberta-finetuned-ner/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/samanta-scratch/Roberta-finetuned-ner/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 57a4662db5e6f535c67185411036d765108189e658324f365fbc10ae7d7455da
- Size of remote file:
- 5.3 kB
- SHA256:
- 0259cb9395471ea793abece470febfe6e37b9658c76abb83ed569672bd871ada
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