Instructions to use microsoft/Multilingual-MiniLM-L12-H384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/Multilingual-MiniLM-L12-H384 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="microsoft/Multilingual-MiniLM-L12-H384")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("microsoft/Multilingual-MiniLM-L12-H384", dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Canwen Xu commited on
Commit ·
f8a8e50
1
Parent(s): eb23326
Fix tokenizer
Browse files- config.json +1 -0
config.json
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@@ -1,5 +1,6 @@
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{
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"attention_probs_dropout_prob": 0.1,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 384,
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{
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"attention_probs_dropout_prob": 0.1,
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"tokenizer_class": "XLMRobertaTokenizer",
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 384,
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