Instructions to use Taykhoom/mRNA-FM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Taykhoom/mRNA-FM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Taykhoom/mRNA-FM", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Taykhoom/mRNA-FM", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer_config.json with huggingface_hub
Browse files- tokenizer_config.json +8 -2
tokenizer_config.json
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"model_max_length": 1024,
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"pad_token": "<pad>",
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"tokenizer_class": "RnaFmTokenizer",
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"unk_token": "<unk>"
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"model_max_length": 1024,
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"pad_token": "<pad>",
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"tokenizer_class": "RnaFmTokenizer",
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"unk_token": "<unk>",
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"auto_map": {
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"AutoTokenizer": [
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"tokenization_rnafm.RnaFmTokenizer",
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null
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]
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}
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}
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