Instructions to use DarcyT/chatglm2-6b-qlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DarcyT/chatglm2-6b-qlora with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="DarcyT/chatglm2-6b-qlora", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DarcyT/chatglm2-6b-qlora", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a88e51c635c345c39c0e2f5e556071f1386e392b1c971069047e5d087b01ca3
- Size of remote file:
- 1.93 GB
- SHA256:
- 369ccd88ceeb9d213ebc216dcb08fbb9da5af3c2579e350292b664ca8f21e37f
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