Instructions to use stanrom/internlm-xcomposer-7b-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stanrom/internlm-xcomposer-7b-4bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="stanrom/internlm-xcomposer-7b-4bit", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("stanrom/internlm-xcomposer-7b-4bit", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from stanrom/internlm-xcomposer-7b-4bit: direct link, hf CLI and curl.
- Browser
- Download file 1.66 MB
-
https://huggingface.co/stanrom/internlm-xcomposer-7b-4bit/resolve/main/tokenizer.model
- Command line
-
hf download hf://stanrom/internlm-xcomposer-7b-4bit/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/stanrom/internlm-xcomposer-7b-4bit/resolve/main/tokenizer.model
1.66 MB
- Xet hash:
- 44065d9f4d8346c13b2753a451d1005b05e032be57ab4468bf33a8d5cbe075b4
- Size of remote file:
- 1.66 MB
- SHA256:
- 21ff673031fd4187f19721a86af4caa6a4deb1f3c2db284f763de3e53bd8f741
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