Token Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use rlimonta/ner_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rlimonta/ner_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rlimonta/ner_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("rlimonta/ner_model") model = AutoModelForTokenClassification.from_pretrained("rlimonta/ner_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from rlimonta/ner_model: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/rlimonta/ner_model/resolve/main/training_args.bin
- Command line
-
hf download hf://rlimonta/ner_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/rlimonta/ner_model/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- 06965677841d82448a7407eb5e6b77f5b89865f098a01e68e8eddb06b4053835
- Size of remote file:
- 5.84 kB
- SHA256:
- 816ffecf01cc2cc4007ca1a75bc897c544b09764c3a461f09770d9e75a4daee6
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