Instructions to use klcsp/llama2-13b-lora-coding-11-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use klcsp/llama2-13b-lora-coding-11-v1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-13b-hf") model = PeftModel.from_pretrained(base_model, "klcsp/llama2-13b-lora-coding-11-v1") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from klcsp/llama2-13b-lora-coding-11-v1: direct link, hf CLI and curl.
- Browser
- Download file 5.69 kB
-
https://huggingface.co/klcsp/llama2-13b-lora-coding-11-v1/resolve/main/training_args.bin
- Command line
-
hf download hf://klcsp/llama2-13b-lora-coding-11-v1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/klcsp/llama2-13b-lora-coding-11-v1/resolve/main/training_args.bin
5.69 kB
- Xet hash:
- 77de7c38cc4acf3e0804ce189768724d3f4e6b1235f006c75a8d7f1309fbc25a
- Size of remote file:
- 5.69 kB
- SHA256:
- 3b2c12644a174ff293a5898dfc99eecb6403ee00825a0313f054b49ba0cca21f
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