Instructions to use ZeroUniqueness/qlora-llama-2-13b-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ZeroUniqueness/qlora-llama-2-13b-code with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/workspace/webui/models/TheBloke_Llama-2-13B-fp16") model = PeftModel.from_pretrained(base_model, "ZeroUniqueness/qlora-llama-2-13b-code") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-7500/optimizer.pt from ZeroUniqueness/qlora-llama-2-13b-code: direct link, hf CLI and curl.
- Browser
- Download file 1 GB
-
https://huggingface.co/ZeroUniqueness/qlora-llama-2-13b-code/resolve/main/checkpoint-7500/optimizer.pt
- Command line
-
hf download hf://ZeroUniqueness/qlora-llama-2-13b-code/checkpoint-7500/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/ZeroUniqueness/qlora-llama-2-13b-code/resolve/main/checkpoint-7500/optimizer.pt
1 GB
- Xet hash:
- 235d36d6552f415680985a51293a14e3ffe23e903f2268d4b1d493fcf9a99033
- Size of remote file:
- 1 GB
- SHA256:
- 0fbb0b5a10201f46c10a18c381ad9781e7f0c8efb247be7229f7b7a1d0f59669
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