Instructions to use devansvd/bert-model-test-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devansvd/bert-model-test-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="devansvd/bert-model-test-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("devansvd/bert-model-test-2") model = AutoModelForTokenClassification.from_pretrained("devansvd/bert-model-test-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitattributes from devansvd/bert-model-test-2: direct link, hf CLI and curl.
- Browser
- Download file 429 Bytes
-
https://huggingface.co/devansvd/bert-model-test-2/resolve/refs%2Fpr%2F1/.gitattributes
- Command line
-
hf download hf://devansvd/bert-model-test-2@refs/pr/1/.gitattributes
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curl -L -o .gitattributes https://huggingface.co/devansvd/bert-model-test-2/resolve/refs%2Fpr%2F1/.gitattributes
429 Bytes
| eval_results_ner.txt filter=lfs diff=lfs merge=lfs -text | |
| pytorch_model.bin filter=lfs diff=lfs merge=lfs -text | |
| special_tokens_map.json filter=lfs diff=lfs merge=lfs -text | |
| tokenizer_config.json filter=lfs diff=lfs merge=lfs -text | |
| training_args.bin filter=lfs diff=lfs merge=lfs -text | |
| vocab.txt filter=lfs diff=lfs merge=lfs -text | |
| *.msgpack filter=lfs diff=lfs merge=lfs -text | |
| model.safetensors filter=lfs diff=lfs merge=lfs -text | |