Instructions to use isbondarev/MiniCPM4-8B-test-adv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use isbondarev/MiniCPM4-8B-test-adv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="isbondarev/MiniCPM4-8B-test-adv", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("isbondarev/MiniCPM4-8B-test-adv", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f15194082adb5a8487f4d096130298abf3c880ee6f65d67ae4e70cb0cb812f82
- Size of remote file:
- 1.18 MB
- SHA256:
- bb74d51116831c3bf65db812c553f94ab0c88dcf97a5bbb37e3504f6d359c530
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