Text Classification
Transformers
Safetensors
bert
code
l3
repo-state-grounding
repositories
repository-library
repository_library_search_stack
research-library
text-embeddings-inference
Instructions to use PeytonT/repo-state-grounding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PeytonT/repo-state-grounding with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PeytonT/repo-state-grounding")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PeytonT/repo-state-grounding") model = AutoModelForSequenceClassification.from_pretrained("PeytonT/repo-state-grounding", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from PeytonT/repo-state-grounding: direct link, hf CLI and curl.
- Browser
- Download file 5.78 kB
-
https://huggingface.co/PeytonT/repo-state-grounding/resolve/main/training_args.bin
- Command line
-
hf download hf://PeytonT/repo-state-grounding/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/PeytonT/repo-state-grounding/resolve/main/training_args.bin
5.78 kB
- Xet hash:
- 0c097248b971be0b137ecba2638cc30b826e3115d70acbef48d8277286f416dd
- Size of remote file:
- 5.78 kB
- SHA256:
- ae227a38a9061bb7e1c2cbd4834d6b65ea3d754cc58a7e4aef9b77c14edf90ef
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