Feature Extraction
PEFT
Safetensors
a1
abstract-code-relevance-pairs
repository-library
research-library
t2_abstract
Instructions to use PeytonT/abstract-code-relevance-pairs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use PeytonT/abstract-code-relevance-pairs with PEFT:
from peft import PeftModel from transformers import AutoModel base_model = AutoModel.from_pretrained("meta-llama/Llama-3.2-1B") model = PeftModel.from_pretrained(base_model, "PeytonT/abstract-code-relevance-pairs") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from PeytonT/abstract-code-relevance-pairs: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/PeytonT/abstract-code-relevance-pairs/resolve/main/tokenizer.json
- Command line
-
hf download hf://PeytonT/abstract-code-relevance-pairs/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/PeytonT/abstract-code-relevance-pairs/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- ba2c6ea26347da32e694706428b087aaa4852052f55a6d968f9ce33c98531991
- Size of remote file:
- 17.2 MB
- SHA256:
- 30992ead73e47f7c13b7f78241657e0306ee446ef8bb7150ecf6c551a090feb0
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