Instructions to use q-future/one-align with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use q-future/one-align with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="q-future/one-align", trust_remote_code=True) pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("q-future/one-align", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload config.json with huggingface_hub
Browse files- config.json +1 -0
config.json
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{
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"_name_or_path": "q-future/one-align",
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"architectures": [
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"MPLUGOwl2LlamaForCausalLM"
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],
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{
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"_name_or_path": "q-future/one-align",
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"model_type": "mplug_owl2",
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"architectures": [
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"MPLUGOwl2LlamaForCausalLM"
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],
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