Instructions to use eabdullin/internlm2-math-20b-awq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eabdullin/internlm2-math-20b-awq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="eabdullin/internlm2-math-20b-awq", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("eabdullin/internlm2-math-20b-awq", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65cf0b8483958a55e734ea4b07a95a87cf09b216c4231046200f150325ae99ab
- Size of remote file:
- 335 kB
- SHA256:
- b5c81a89347f5767b5370cfd2ea2e2bbc7feb83db5d240833765f813362182fb
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