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")# 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") - Notebooks
- Google Colab
- Kaggle
| 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 | |