Instructions to use llm-jp/Jagle-VL-2.2B-Jagle-FineVision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use llm-jp/Jagle-VL-2.2B-Jagle-FineVision with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="llm-jp/Jagle-VL-2.2B-Jagle-FineVision", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("llm-jp/Jagle-VL-2.2B-Jagle-FineVision", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +2 -2
config.json
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"LLMjpVLModel"
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],
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"auto_map": {
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"AutoConfig": "configuration_llmjpvl.
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"AutoModel": "modeling_llmjpvl.
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"AutoProcessor": "processing_llmjpvl.LLMjpVLProcessor"
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},
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"downsample_ratio": 0.5,
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"LLMjpVLModel"
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],
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"auto_map": {
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"AutoConfig": "configuration_llmjpvl.LLMjpVLConfig",
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"AutoModel": "modeling_llmjpvl.LLMjpVLModel",
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"AutoProcessor": "processing_llmjpvl.LLMjpVLProcessor"
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},
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"downsample_ratio": 0.5,
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