Instructions to use joycejiang/llama2-13B-qlora-codex-kbgraph-100-rs0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use joycejiang/llama2-13B-qlora-codex-kbgraph-100-rs0 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, "joycejiang/llama2-13B-qlora-codex-kbgraph-100-rs0") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from joycejiang/llama2-13B-qlora-codex-kbgraph-100-rs0: direct link, hf CLI and curl.
- Browser
- Download file 26.3 MB
-
https://huggingface.co/joycejiang/llama2-13B-qlora-codex-kbgraph-100-rs0/resolve/main/adapter_model.bin
- Command line
-
hf download hf://joycejiang/llama2-13B-qlora-codex-kbgraph-100-rs0/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/joycejiang/llama2-13B-qlora-codex-kbgraph-100-rs0/resolve/main/adapter_model.bin
26.3 MB
- Xet hash:
- 6217dc6ecfc8d5ca8e6dfae610ed86158b02c2f089427cfac2147fc5880d527f
- Size of remote file:
- 26.3 MB
- SHA256:
- c63a9dedc575ce70e1372f434effb70b905a80bc59465a34b60a7f35ad71bfcd
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