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:
- 5df4936f3307a528afe196f079b58335175c822a48e2e1ccfc85032e837ca2ca
- Size of remote file:
- 3.77 kB
- SHA256:
- 6ef94eb9095d3ed99019d1c40ba4545103db565388e37d3454e5f164575dd0a2
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