Instructions to use immanuelpeter/MiniMax-M3.1-Flash-Vision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use immanuelpeter/MiniMax-M3.1-Flash-Vision with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="immanuelpeter/MiniMax-M3.1-Flash-Vision")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("immanuelpeter/MiniMax-M3.1-Flash-Vision") model = AutoModel.from_pretrained("immanuelpeter/MiniMax-M3.1-Flash-Vision", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Synchronize maintained vision bundle layout and manifest
Browse files- README.md +1 -0
- export_manifest.json +1 -1
README.md
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## Usage
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See [`examples/inference.py`](examples/inference.py) for image feature extraction.
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Forward one image per call: the native HF attention couples images in a single call.
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## Validation
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## Usage
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See [`examples/inference.py`](examples/inference.py) for image feature extraction.
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Forward images independently to avoid attention coupling in packed batches.
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Forward one image per call: the native HF attention couples images in a single call.
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## Validation
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export_manifest.json
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"LICENSE": "8c4978e3e0fe0349ff929cc8450463cba3039c4c9fc144d8bd5382ab00df247a",
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"LICENSE-CODE": "149f05ce186198084c9abd6af8e76e108ba7e507446a19ee5a2ffd694f69f525",
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"NOTICE": "19d19379d439b6dc2614476bb50b170fbe382a58f3a84ec67ff9bcd4e212d626",
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"README.md": "
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"config.json": "9c3a6dac0654055594fdde1f148400331f3e55cb72ffe1b7a6806db07ab93a79",
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"examples/inference.py": "fcde5470ba4e9fce0730f544f4f3b7669bf4f9bdcaf556223cebc4ed67ef1c5a",
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"model.safetensors": "95e3731e26887d066a0b2291a1574da40a36aba5ba43e476746b9c16a64bcf08",
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"LICENSE": "8c4978e3e0fe0349ff929cc8450463cba3039c4c9fc144d8bd5382ab00df247a",
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"LICENSE-CODE": "149f05ce186198084c9abd6af8e76e108ba7e507446a19ee5a2ffd694f69f525",
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"NOTICE": "19d19379d439b6dc2614476bb50b170fbe382a58f3a84ec67ff9bcd4e212d626",
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+
"README.md": "8e22a8fa2a0afdcaa1409f9a77366c1ba2e7bb1d6a4dae1a144627f068cc1e41",
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"config.json": "9c3a6dac0654055594fdde1f148400331f3e55cb72ffe1b7a6806db07ab93a79",
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"examples/inference.py": "fcde5470ba4e9fce0730f544f4f3b7669bf4f9bdcaf556223cebc4ed67ef1c5a",
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"model.safetensors": "95e3731e26887d066a0b2291a1574da40a36aba5ba43e476746b9c16a64bcf08",
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