Instructions to use dusersad12/OrionNet-BestCheckpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/OrionNet-BestCheckpoint with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dusersad12/OrionNet-BestCheckpoint")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dusersad12/OrionNet-BestCheckpoint") model = AutoModel.from_pretrained("dusersad12/OrionNet-BestCheckpoint", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dusersad12/OrionNet-BestCheckpoint: direct link, hf CLI and curl.
- Browser
- Download file 27 Bytes
-
https://huggingface.co/dusersad12/OrionNet-BestCheckpoint/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dusersad12/OrionNet-BestCheckpoint/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dusersad12/OrionNet-BestCheckpoint/resolve/main/pytorch_model.bin
27 Bytes
- Xet hash:
- a3c617285529dba12c06c14ed4e0d0a1736fd40152b0e43b0117ecdf3b58107e
- Size of remote file:
- 27 Bytes
- SHA256:
- 435cf3ea9df17de2617fcd0bfa81f81845df881d965d8fc809b1a0a585691382
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