Instructions to use pogtador/codebert-fine-tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pogtador/codebert-fine-tuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="pogtador/codebert-fine-tuned")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("pogtador/codebert-fine-tuned") model = AutoModelForMaskedLM.from_pretrained("pogtador/codebert-fine-tuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from pogtador/codebert-fine-tuned: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/pogtador/codebert-fine-tuned/resolve/main/training_args.bin
- Command line
-
hf download hf://pogtador/codebert-fine-tuned/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/pogtador/codebert-fine-tuned/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 2646ed4f166f11aabaea90b680f1172e1713772910deda37de5cf9e1b31e1bd0
- Size of remote file:
- 5.3 kB
- SHA256:
- 412bf79740bb33ed4ee73070b1724246a52a1243504129b57ecf7e9bd3db3bda
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