Instructions to use tiny-random/minicpm-v-4.6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tiny-random/minicpm-v-4.6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="tiny-random/minicpm-v-4.6")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("tiny-random/minicpm-v-4.6") model = AutoModel.from_pretrained("tiny-random/minicpm-v-4.6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 362054e70995b541e6dc3a6c84729e38ce056016b18d6f80a907f7b2492b3583
- Size of remote file:
- 20 MB
- SHA256:
- 33861e37bb955af1e3f3061182b820f347eba2b9c2c1011c82794bf0d6e77b54
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