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 from transformers import pipeline pipe = pipeline("visual-question-answering", model="internlm/internlm-xcomposer2d5-7b", trust_remote_code=True)# 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
- Xet hash:
- 53eb688cbafd02cfc64bd5129dc00046dbe9425dbb3ca4cf7c08a456122ad2d7
- Size of remote file:
- 9.75 MB
- SHA256:
- 336a838f4a78e150826be608dae69de59d50948c3d2b71760e096ae764154bdc
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