Instructions to use dd101bb/latentRM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dd101bb/latentRM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dd101bb/latentRM")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("dd101bb/latentRM") model = AutoModelForTokenClassification.from_pretrained("dd101bb/latentRM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Update pipeline tag and add license
Verified signatureThis PR updates the model card to: - Change the `pipeline_tag` from `token-classification` to `feature-extraction` to better reflect the model's function as a learned scorer for latent reasoning. - Add the `license` tag, explicitly stating it as Apache-2.0.fa08fbb
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Update README.md
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Upload COCONUTGPT2ForTokenClassification
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