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)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("DataCanvas/MMAlaya", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a955ccd1f914f852c6abb450c21d21ed9bdb6288b5e353fadb782111c4c2b45
- Size of remote file:
- 1.2 MB
- SHA256:
- c9a4a06f4a6be7218225021f4df89e09a0b14777bff7767712420eddb7e9b5ee
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