Sentence Similarity
Transformers
PyTorch
mt5
feature-extraction
cross-lingual
multilingual
question-answering
retrieval
variational
custom_code
Instructions to use jwieting/vmsst with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jwieting/vmsst with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("jwieting/vmsst", trust_remote_code=True) model = AutoModel.from_pretrained("jwieting/vmsst", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
Fix AutoModel map path
#1
by freddyheppell - opened
- config.json +1 -1
config.json
CHANGED
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@@ -4,7 +4,7 @@
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"MT5EncoderWithProjection"
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],
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"auto_map": {
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-
"AutoModel": "
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},
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"d_ff": 2816,
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"d_kv": 64,
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"MT5EncoderWithProjection"
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],
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"auto_map": {
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+
"AutoModel": "modeling_vmsst.MT5EncoderWithProjection"
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},
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"d_ff": 2816,
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"d_kv": 64,
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