Instructions to use namesarnav/causalbench_code-t5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use namesarnav/causalbench_code-t5-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="namesarnav/causalbench_code-t5-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("namesarnav/causalbench_code-t5-base") model = AutoModelForSequenceClassification.from_pretrained("namesarnav/causalbench_code-t5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from namesarnav/causalbench_code-t5-base: direct link, hf CLI and curl.
- Browser
- Download file 5.91 kB
-
https://huggingface.co/namesarnav/causalbench_code-t5-base/resolve/main/training_args.bin
- Command line
-
hf download hf://namesarnav/causalbench_code-t5-base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/namesarnav/causalbench_code-t5-base/resolve/main/training_args.bin
5.91 kB
- Xet hash:
- d10818bb908f6e3218be3f6b2db012d84f6ebb9b551e0815be9d13352dfb6c71
- Size of remote file:
- 5.91 kB
- SHA256:
- 7c0629125cb777b25684fbe6f60a310898988eb697c50d70d61de3141b9cd5fc
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