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
Download NOTICE from immanuelpeter/MiniMax-M3.1-Flash-Vision: direct link, hf CLI and curl.
- Browser
- Download file 529 Bytes
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https://huggingface.co/immanuelpeter/MiniMax-M3.1-Flash-Vision/resolve/main/NOTICE
- Command line
-
hf download hf://immanuelpeter/MiniMax-M3.1-Flash-Vision/NOTICE
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curl -L -o NOTICE https://huggingface.co/immanuelpeter/MiniMax-M3.1-Flash-Vision/resolve/main/NOTICE
529 Bytes
| MiniMax-M3.1-Flash Vision | |
| Extracted from MiniMaxAI/MiniMax-M3.1-Flash at 54e4e69dfc452b1e94a426c24a4fdeeaa8e3ad5e. | |
| Copyright MiniMax. Distributed under the accompanying MiniMax Community License. | |
| Tower and Projector tensors are preserved exactly. State-dictionary keys are adapted for native Transformers classes. | |
| This is a standalone vision extraction, not the complete language model. | |
| projector.py and examples/inference.py are original vision-tower-bench helper code. | |
| Copyright (c) 2026 Immanuel Peter. MIT; see LICENSE-CODE. | |