Instructions to use radna/mini_intern_chat_triton with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use radna/mini_intern_chat_triton with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="radna/mini_intern_chat_triton", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("radna/mini_intern_chat_triton", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -151,7 +151,7 @@ def load_image(image_file, input_size=448, max_num=6):
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return pixel_values
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path = "OpenGVLab/Mini-InternVL-Chat-
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model = AutoModel.from_pretrained(
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path,
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torch_dtype=torch.bfloat16,
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return pixel_values
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path = "OpenGVLab/Mini-InternVL-Chat-4B-V1-5"
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model = AutoModel.from_pretrained(
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path,
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torch_dtype=torch.bfloat16,
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