Instructions to use tiennvcs/distilbert-base-uncased-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiennvcs/distilbert-base-uncased-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="tiennvcs/distilbert-base-uncased-finetuned-ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("tiennvcs/distilbert-base-uncased-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("tiennvcs/distilbert-base-uncased-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tiennvcs/distilbert-base-uncased-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 266 MB
-
https://huggingface.co/tiennvcs/distilbert-base-uncased-finetuned-ner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tiennvcs/distilbert-base-uncased-finetuned-ner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tiennvcs/distilbert-base-uncased-finetuned-ner/resolve/main/pytorch_model.bin
266 MB
- Xet hash:
- 8c0eeae814980d167f5fc3b60b6f1094b1582e494a239e820c71f886a6303d26
- Size of remote file:
- 266 MB
- SHA256:
- e66de1b64b89ab69699257cab5a39f825bae183a06dd69e67b959fd2988ee0b1
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