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:
- 260b1ea21f57a8d704cd1f7615c4dae174b65ea784abb9543c825d41152b6d33
- Size of remote file:
- 9.97 GB
- SHA256:
- 4b50f5b8df413dade11f624f55ea317bb0158baee38f1ee5f8ed37cbe93f1ba7
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