Instructions to use Saugatkafley/bloom-1b1-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Saugatkafley/bloom-1b1-onnx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Saugatkafley/bloom-1b1-onnx")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Saugatkafley/bloom-1b1-onnx") model = AutoModel.from_pretrained("Saugatkafley/bloom-1b1-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.onnx_data from Saugatkafley/bloom-1b1-onnx: direct link, hf CLI and curl.
- Browser
- Download file 4.26 GB
-
https://huggingface.co/Saugatkafley/bloom-1b1-onnx/resolve/main/model.onnx_data
- Command line
-
hf download hf://Saugatkafley/bloom-1b1-onnx/model.onnx_data
-
curl -L -o model.onnx_data https://huggingface.co/Saugatkafley/bloom-1b1-onnx/resolve/main/model.onnx_data
4.26 GB
- Xet hash:
- 903406cf6b73d1a982bbbdb04a25590c21db5d1cefb89dfd99228173381175e2
- Size of remote file:
- 4.26 GB
- SHA256:
- f7f5bc52b97a65f0f79bf0ed48fa3f96cdc55f58c9cc040c7edc3ed180d16b34
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