Instructions to use dusersad12/NimbusModel-ReleaseRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/NimbusModel-ReleaseRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dusersad12/NimbusModel-ReleaseRepo")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dusersad12/NimbusModel-ReleaseRepo") model = AutoModel.from_pretrained("dusersad12/NimbusModel-ReleaseRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dusersad12/NimbusModel-ReleaseRepo: direct link, hf CLI and curl.
- Browser
- Download file 27 Bytes
-
https://huggingface.co/dusersad12/NimbusModel-ReleaseRepo/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dusersad12/NimbusModel-ReleaseRepo/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dusersad12/NimbusModel-ReleaseRepo/resolve/main/pytorch_model.bin
27 Bytes
- Xet hash:
- 8e8ca0c5b370085e2a48676b2eb76dfe343ba095b820fc6c8f69fe6869b07e3d
- Size of remote file:
- 27 Bytes
- SHA256:
- cf2ebc03c8a01864881971490e182d8b00d91cdc614abdd0bafe5baff268f628
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