Instructions to use SkyR/hing-mbert-ours-run-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SkyR/hing-mbert-ours-run-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SkyR/hing-mbert-ours-run-5")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SkyR/hing-mbert-ours-run-5") model = AutoModelForSequenceClassification.from_pretrained("SkyR/hing-mbert-ours-run-5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SkyR/hing-mbert-ours-run-5: direct link, hf CLI and curl.
- Browser
- Download file 711 MB
-
https://huggingface.co/SkyR/hing-mbert-ours-run-5/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SkyR/hing-mbert-ours-run-5/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SkyR/hing-mbert-ours-run-5/resolve/main/pytorch_model.bin
711 MB
- Xet hash:
- 4fa084a0b45fa6696c17a17e9002b69fd650cd2af411db25d7ee6b91f58bb29f
- Size of remote file:
- 711 MB
- SHA256:
- be52fcf64057d90d4a46610b285c69b1dcf2b048c92bc8d56072488f5b73bdef
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