Instructions to use PopularPenguin/CodeLlama-TextToSparql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use PopularPenguin/CodeLlama-TextToSparql with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("codellama/CodeLlama-7b-hf") model = PeftModel.from_pretrained(base_model, "PopularPenguin/CodeLlama-TextToSparql") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from PopularPenguin/CodeLlama-TextToSparql: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/PopularPenguin/CodeLlama-TextToSparql/resolve/main/training_args.bin
- Command line
-
hf download hf://PopularPenguin/CodeLlama-TextToSparql/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/PopularPenguin/CodeLlama-TextToSparql/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 13465e6e7b3e552f5b1013c79c1b3df721ef6e0550753f1d01c348ec141b3684
- Size of remote file:
- 5.18 kB
- SHA256:
- 3af00dc07662d679f37c0cb21380bf9e0fc948a365c5c959d45b39dc10ba67fd
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