Instructions to use internlm/internlm-xcomposer2d5-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use internlm/internlm-xcomposer2d5-7b with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "visual-question-answering" 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("visual-question-answering", model="internlm/internlm-xcomposer2d5-7b", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("internlm/internlm-xcomposer2d5-7b", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download examples/test.py from internlm/internlm-xcomposer2d5-7b: direct link, hf CLI and curl.
- Browser
- Download file 0 Bytes
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https://huggingface.co/internlm/internlm-xcomposer2d5-7b/resolve/main/examples/test.py
- Command line
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hf download hf://internlm/internlm-xcomposer2d5-7b/examples/test.py
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curl -L -o test.py https://huggingface.co/internlm/internlm-xcomposer2d5-7b/resolve/main/examples/test.py
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