Instructions to use blekkk/ner_411 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use blekkk/ner_411 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="blekkk/ner_411")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("blekkk/ner_411") model = AutoModelForTokenClassification.from_pretrained("blekkk/ner_411", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from blekkk/ner_411: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/blekkk/ner_411/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://blekkk/ner_411/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/blekkk/ner_411/resolve/main/pytorch_model.bin
1.11 GB
- Xet hash:
- 67cee753f7c05845e99d7b9bbebe40673de6d3efb5c07fae3d25a99c422ef63c
- Size of remote file:
- 1.11 GB
- SHA256:
- 019e399944c60066e950e76f1f8aaadd8546ae032169504fc81301081966a8c2
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