Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use whoisjones/finerweb-binary-classifier-mdeberta-gemma3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whoisjones/finerweb-binary-classifier-mdeberta-gemma3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="whoisjones/finerweb-binary-classifier-mdeberta-gemma3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("whoisjones/finerweb-binary-classifier-mdeberta-gemma3") model = AutoModelForSequenceClassification.from_pretrained("whoisjones/finerweb-binary-classifier-mdeberta-gemma3") - Notebooks
- Google Colab
- Kaggle
Improve model card: Add pipeline tag, paper/code links, and usage example
#1
by nielsr HF Staff - opened
This PR significantly improves the model card for finerweb-binary-classifier-mdeberta-gemma3 by:
- Adding the
pipeline_tag: text-classificationto the metadata, enabling easier discovery on the Hub and activating the inference widget. - Expanding the
tagsto includetext-classification,named-entity-recognition, anddeberta-v2for better categorization. - Adding a direct link to the paper FiNERweb: Datasets and Artifacts for Scalable Multilingual Named Entity Recognition.
- Providing a link to the associated GitHub code repository: https://github.com/whoisjones/FiNERweb-code.
- Including a link to the Hugging Face Collection for the project: https://huggingface.co/collections/whoisjones/finerweb.
- Populating the "Model description", "Intended uses & limitations", and "Training and evaluation data" sections with detailed information from the paper abstract and GitHub README.
- Including a detailed Python sample usage snippet directly from the GitHub repository, demonstrating how to load and use the model with
transformers. - Adding the BibTeX citation for the paper.
Please review and merge if everything looks good.