Instructions to use Taykhoom/mRNABERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Taykhoom/mRNABERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Taykhoom/mRNABERT", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Taykhoom/mRNABERT", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("Taykhoom/mRNABERT", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
Bump model_max_length to 10000 (matches dnabert2/dnaberts; MosaicBERT/ALiBi extrapolates)
Browse files- tokenizer_config.json +7 -4
tokenizer_config.json
CHANGED
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@@ -4,9 +4,9 @@
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"do_basic_tokenize": true,
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"do_lower_case": false,
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"mask_token": "[MASK]",
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"max_len":
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"max_length":
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"model_max_length":
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"never_split": null,
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"pad_to_multiple_of": null,
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"pad_token": "[PAD]",
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@@ -17,7 +17,10 @@
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"auto_map": {
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"AutoTokenizer": [
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},
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"tokenizer_class": "MRNABERTTokenizer",
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"truncation_side": "right",
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"do_basic_tokenize": true,
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"do_lower_case": false,
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"mask_token": "[MASK]",
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"max_len": 10000,
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"max_length": 10000,
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"model_max_length": 10000,
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"never_split": null,
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"pad_to_multiple_of": null,
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"pad_token": "[PAD]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"auto_map": {
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"AutoTokenizer": [
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"tokenization_mrnabert.MRNABERTTokenizer",
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null
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]
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},
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"tokenizer_class": "MRNABERTTokenizer",
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"truncation_side": "right",
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