Instructions to use ZZZZCCCC/codebert_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZZZZCCCC/codebert_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ZZZZCCCC/codebert_3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ZZZZCCCC/codebert_3") model = AutoModelForMaskedLM.from_pretrained("ZZZZCCCC/codebert_3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ZZZZCCCC/codebert_3: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/ZZZZCCCC/codebert_3/resolve/main/training_args.bin
- Command line
-
hf download hf://ZZZZCCCC/codebert_3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ZZZZCCCC/codebert_3/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 97e604644a28919f01dbf088addf5c94c49874e9fbc99c3c2e0a4ed807a21ced
- Size of remote file:
- 4.92 kB
- SHA256:
- 431307a03c458331634a84eb491bc07cd92e317229ca5443b4a87541022435ca
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