Instructions to use malteklaes/based-CodeBERTa-language-id-llm-module with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use malteklaes/based-CodeBERTa-language-id-llm-module with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="malteklaes/based-CodeBERTa-language-id-llm-module")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("malteklaes/based-CodeBERTa-language-id-llm-module") model = AutoModelForSequenceClassification.from_pretrained("malteklaes/based-CodeBERTa-language-id-llm-module") - Notebooks
- Google Colab
- Kaggle
updated model on 2024-04-14, 22:41:18
Browse files- config.json +2 -2
- model.safetensors +2 -2
config.json
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"go": 0,
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"python": 4,
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"ruby": 5
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"cpp" : 6
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"cpp": 6,
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"go": 0,
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"java": 1,
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"javascript": 2,
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"php": 3,
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"python": 4,
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"ruby": 5
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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size 333837580
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