Instructions to use G-WOO/200mil-CodeBERTa-small-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use G-WOO/200mil-CodeBERTa-small-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="G-WOO/200mil-CodeBERTa-small-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("G-WOO/200mil-CodeBERTa-small-v1") model = AutoModelForSequenceClassification.from_pretrained("G-WOO/200mil-CodeBERTa-small-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from G-WOO/200mil-CodeBERTa-small-v1: direct link, hf CLI and curl.
- Browser
- Download file 334 MB
-
https://huggingface.co/G-WOO/200mil-CodeBERTa-small-v1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://G-WOO/200mil-CodeBERTa-small-v1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/G-WOO/200mil-CodeBERTa-small-v1/resolve/main/pytorch_model.bin
334 MB
- Xet hash:
- d1ca7533d975bac93e2b18a9f948ebfdb9887e233464e2f4b6d169e302e73713
- Size of remote file:
- 334 MB
- SHA256:
- d2dafb7ec91e7db10f3eb3991df0113be7daf8a0b5508f0dbcd62e1ad6d2cb6c
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