Instructions to use sanjay7178/bert-finetuned-ner-accelerate with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sanjay7178/bert-finetuned-ner-accelerate with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sanjay7178/bert-finetuned-ner-accelerate")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("sanjay7178/bert-finetuned-ner-accelerate") model = AutoModelForTokenClassification.from_pretrained("sanjay7178/bert-finetuned-ner-accelerate", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sanjay7178/bert-finetuned-ner-accelerate: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/sanjay7178/bert-finetuned-ner-accelerate/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sanjay7178/bert-finetuned-ner-accelerate/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sanjay7178/bert-finetuned-ner-accelerate/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- ba60dc6c23ff53bdf84c40fa93dc683fde572be205cf1d0411d77d142a192dd1
- Size of remote file:
- 431 MB
- SHA256:
- 6367686d99b1a32542a6ef5ba534be7d36eadbd768e98f16fe812598b2e8a991
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