Instructions to use hf-internal-testing/tiny-random-m2m_100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-m2m_100 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-m2m_100", dtype="auto") - Notebooks
- Google Colab
- Kaggle
revert max_position_embeddings as some weights depend on it.
Browse files- config.json +1 -1
config.json
CHANGED
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@@ -18,7 +18,7 @@
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"gradient_checkpointing": false,
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| 19 |
"init_std": 0.02,
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"is_encoder_decoder": true,
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-
"max_position_embeddings":
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"model_type": "m2m_100",
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"num_hidden_layers": 2,
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| 24 |
"pad_token_id": 1,
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| 18 |
"gradient_checkpointing": false,
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| 19 |
"init_std": 0.02,
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| 20 |
"is_encoder_decoder": true,
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+
"max_position_embeddings": 20,
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"model_type": "m2m_100",
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| 23 |
"num_hidden_layers": 2,
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| 24 |
"pad_token_id": 1,
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