Instructions to use tiny-random/kimi-k2.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiny-random/kimi-k2.5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="tiny-random/kimi-k2.5", trust_remote_code=True)# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("tiny-random/kimi-k2.5", trust_remote_code=True) model = AutoModel.from_pretrained("tiny-random/kimi-k2.5", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6dc6733f1adc4736414ea6d0701a58fb5ab395fa3cc374230ccb2c59a13dd0db
- Size of remote file:
- 6.49 MB
- SHA256:
- 80a09d95543a7a7eee8f6ca664534a52d2ee476627264a81bf48da66e9d5df45
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