Instructions to use dada22231/def46a41-c837-4f28-8ada-c302c06a06bc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/def46a41-c837-4f28-8ada-c302c06a06bc with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("The-matt/llama2_ko-7b_distinctive-snowflake-182_1060") model = PeftModel.from_pretrained(base_model, "dada22231/def46a41-c837-4f28-8ada-c302c06a06bc") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dada22231/def46a41-c837-4f28-8ada-c302c06a06bc: direct link, hf CLI and curl.
- Browser
- Download file 6.84 kB
-
https://huggingface.co/dada22231/def46a41-c837-4f28-8ada-c302c06a06bc/resolve/main/training_args.bin
- Command line
-
hf download hf://dada22231/def46a41-c837-4f28-8ada-c302c06a06bc/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dada22231/def46a41-c837-4f28-8ada-c302c06a06bc/resolve/main/training_args.bin
6.84 kB
- Xet hash:
- 45ae2cfbd4397b9631ec1f93c2747544abb1329dde4e9a8d3b8681b41824d322
- Size of remote file:
- 6.84 kB
- SHA256:
- 6277fc8feb16c9c1a0f697c8a709323544ae3beaeabf5d03415ba0cfdb6090ae
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