Instructions to use tcapelle/random-tiny-modernbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tcapelle/random-tiny-modernbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tcapelle/random-tiny-modernbert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tcapelle/random-tiny-modernbert") model = AutoModelForSequenceClassification.from_pretrained("tcapelle/random-tiny-modernbert") - Notebooks
- Google Colab
- Kaggle
Upload TextClassificationPipeline
Browse files- config.json +1 -1
- model.safetensors +1 -1
config.json
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"layer_norm_eps": 1e-05,
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"local_attention": 128,
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"local_rope_theta": 10000.0,
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"max_position_embeddings":
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"mlp_bias": false,
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"mlp_dropout": 0.0,
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"model_type": "modernbert",
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"layer_norm_eps": 1e-05,
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"local_attention": 128,
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"local_rope_theta": 10000.0,
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"max_position_embeddings": 8192,
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"mlp_bias": false,
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"mlp_dropout": 0.0,
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"model_type": "modernbert",
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 6535832
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