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:
- 38cdc5d669c3b516231566e20ea8a162cbc8545d41809a1e91b5c355e3b28090
- Size of remote file:
- 2.22 GB
- SHA256:
- 0880b52a0d27935e83f5b3fef2886d626671adb2e56de9162344c904e368490e
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