Instructions to use decube/all-mpnet-base-v2_O3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use decube/all-mpnet-base-v2_O3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="decube/all-mpnet-base-v2_O3")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("decube/all-mpnet-base-v2_O3") model = AutoModelForMaskedLM.from_pretrained("decube/all-mpnet-base-v2_O3") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): b0c21df
Upload tokenizer
Browse files- tokenizer.json +2 -4
tokenizer.json
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"version": "1.0",
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"version": "1.0",
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"truncation": {
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"max_length": 512,
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"strategy": "LongestFirst",
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"strategy": "BatchLongest",
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"direction": "Right",
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"pad_id": 1,
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