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 +3 -3
config.json
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"MPLUGOwl2LlamaForCausalLM"
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"auto_map": {
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"AutoConfig": "
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"AutoModel": "
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"AutoModelForCausalLM": "
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"attention_bias": false,
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"bos_token_id": 1,
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"MPLUGOwl2LlamaForCausalLM"
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],
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"auto_map": {
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"AutoConfig": "configuration_mplug_owl2.MPLUGOwl2Config",
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"AutoModel": "modeling_mplug_owl2.MPLUGOwl2LlamaForCausalLM",
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"AutoModelForCausalLM": "modeling_mplug_owl2.MPLUGOwl2LlamaForCausalLM"
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},
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"attention_bias": false,
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"bos_token_id": 1,
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