Instructions to use Myashka/MPNet_RM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Myashka/MPNet_RM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Myashka/MPNet_RM")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Myashka/MPNet_RM") model = AutoModel.from_pretrained("Myashka/MPNet_RM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +1 -1
config.json
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@@ -2,7 +2,7 @@
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"_name_or_path": "microsoft/mpnet-base",
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"a_n_loss_weight": 0,
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"architectures": [
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"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"_name_or_path": "microsoft/mpnet-base",
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"a_n_loss_weight": 0,
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"architectures": [
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"MPNetModel"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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