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
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2024.01.23 最终在[MMBench](https://mmbench.opencompass.org.cn)线上测试中文测试集分数为56.9,英文测试集分数为59.8。
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推理可以参考 [inference.py](https://github.com/
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2024.01.23 最终在[MMBench](https://mmbench.opencompass.org.cn)线上测试中文测试集分数为56.9,英文测试集分数为59.8。
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推理可以参考 [inference.py](https://github.com/DataCanvasIO/MMAlaya/blob/main/inference.py)
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