Instructions to use DataCanvas/MMAlaya with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DataCanvas/MMAlaya with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("image-to-text", model="DataCanvas/MMAlaya", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("DataCanvas/MMAlaya", 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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"softmax_scale": null
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},
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"auto_map": {
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"AutoConfig": "
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"AutoModelForCausalLM": "
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},
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"d_model": 4096,
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"emb_pdrop": 0.0,
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"softmax_scale": null
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},
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"auto_map": {
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"AutoConfig": "configuration_mmalaya.MMAlayaMPTConfig",
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"AutoModelForCausalLM": "modeling_mmalaya.MMAlayaMPTForCausalLM"
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},
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"d_model": 4096,
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"emb_pdrop": 0.0,
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