Instructions to use kokovova/5835b2f5-d375-4e43-bd4b-d4f068f9cf54 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kokovova/5835b2f5-d375-4e43-bd4b-d4f068f9cf54 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("dunzhang/stella_en_1.5B_v5") model = PeftModel.from_pretrained(base_model, "kokovova/5835b2f5-d375-4e43-bd4b-d4f068f9cf54") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kokovova/5835b2f5-d375-4e43-bd4b-d4f068f9cf54: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/kokovova/5835b2f5-d375-4e43-bd4b-d4f068f9cf54/resolve/main/training_args.bin
- Command line
-
hf download hf://kokovova/5835b2f5-d375-4e43-bd4b-d4f068f9cf54/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kokovova/5835b2f5-d375-4e43-bd4b-d4f068f9cf54/resolve/main/training_args.bin
6.78 kB
- Xet hash:
- a278e283ae2d1607013835e2e8c1644460620c6d0aa2536e725aa0f5556eef5b
- Size of remote file:
- 6.78 kB
- SHA256:
- e09e24b455d5d9f431c2f7ffae5bb47f6b88042299f5ff5163224e3a24108ad1
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