Instructions to use harpertoken/name with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harpertoken/name with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="harpertoken/name")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("harpertoken/name") model = AutoModelForTokenClassification.from_pretrained("harpertoken/name", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model
Verified signatureThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.94f4807
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Metadata Enhancements:
Niladri DasVerified signatureAdded pipeline_tag: token-classification: Ensures it’s recognized for NER pipelines. Added language: en: Specifies English, improving search and filtering. Added library_name: transformers: Clarifies the framework. Added base_model: bert-base-uncased: Links the pre-trained backbone. Enhanced model-index: Includes the validation loss as a metric, structured for Hugging Face’s UI display. Added widget: Provides an interactive example (optional—remove if you don’t want it). Added nlp tag: Broadens visibility in NLP-related searches. UI Impact: On Hugging Face, this will display the loss under “Metrics,” show the task as NER, and filter better in searches for English NER models. The widget (if kept) lets users test the model directly on the page with your example sentence.6b3acc4
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update model card README.md
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Training in progress, epoch 3
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End of training
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Training in progress, step 1500
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Niladri DasVerified signature9d02162