Instructions to use kokovova/11c561bd-fc4b-4cd2-af7c-6c97ffe633ba with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kokovova/11c561bd-fc4b-4cd2-af7c-6c97ffe633ba with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0") model = PeftModel.from_pretrained(base_model, "kokovova/11c561bd-fc4b-4cd2-af7c-6c97ffe633ba") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kokovova/11c561bd-fc4b-4cd2-af7c-6c97ffe633ba: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/kokovova/11c561bd-fc4b-4cd2-af7c-6c97ffe633ba/resolve/main/training_args.bin
- Command line
-
hf download hf://kokovova/11c561bd-fc4b-4cd2-af7c-6c97ffe633ba/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kokovova/11c561bd-fc4b-4cd2-af7c-6c97ffe633ba/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- d60aab63749cd3cc52b2817970b48914a0f35f9dd565723e69cd9f1c955be6f3
- Size of remote file:
- 6.78 kB
- SHA256:
- 08f0d0b535c76aa79e72826b04ff7259edf81194a884651982bf2dd3d1a05d15
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