Instructions to use internlm/internlm-xcomposer2-4khd-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use internlm/internlm-xcomposer2-4khd-7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="internlm/internlm-xcomposer2-4khd-7b", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("internlm/internlm-xcomposer2-4khd-7b", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a4c47da7243150c3767731d63fb235467573314cb5d40bf5bbd04890d0162a8
- Size of remote file:
- 7.2 GB
- SHA256:
- e021e0caa1ef38c36f0343cc3250eef1092b856847f562ac5ad39100f1e81128
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