Instructions to use namesarnav/causalbench_code-bert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use namesarnav/causalbench_code-bert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="namesarnav/causalbench_code-bert-base-uncased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("namesarnav/causalbench_code-bert-base-uncased") model = AutoModelForSequenceClassification.from_pretrained("namesarnav/causalbench_code-bert-base-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from namesarnav/causalbench_code-bert-base-uncased: direct link, hf CLI and curl.
- Browser
- Download file 5.33 kB
-
https://huggingface.co/namesarnav/causalbench_code-bert-base-uncased/resolve/main/training_args.bin
- Command line
-
hf download hf://namesarnav/causalbench_code-bert-base-uncased/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/namesarnav/causalbench_code-bert-base-uncased/resolve/main/training_args.bin
5.33 kB
- Xet hash:
- ff7f42340da88931cd2cb4849cb4ba6777b553ad416cac6a296e985691caf3eb
- Size of remote file:
- 5.33 kB
- SHA256:
- 408060db342659f61cd333fb7559e735130df2cef64821c0241609ac90d320f3
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