Instructions to use chendelong/ChatGLM-PSP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chendelong/ChatGLM-PSP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="chendelong/ChatGLM-PSP", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("chendelong/ChatGLM-PSP", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6746b248e39f94ad85c0798ab78eb4f24c68dbcbbba3fdfad039dc1458d3b830
- Size of remote file:
- 7.34 MB
- SHA256:
- 4c86296e5dc5d84728d9e60a003c8bb999d6426f4e4c269b9f45b6cf6de88079
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