Instructions to use dimasik1987/e30049b5-cd04-4fe0-b118-8281e9846f5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dimasik1987/e30049b5-cd04-4fe0-b118-8281e9846f5b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("peft-internal-testing/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "dimasik1987/e30049b5-cd04-4fe0-b118-8281e9846f5b") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from dimasik1987/e30049b5-cd04-4fe0-b118-8281e9846f5b: direct link, hf CLI and curl.
- Browser
- Download file 32.6 kB
-
https://huggingface.co/dimasik1987/e30049b5-cd04-4fe0-b118-8281e9846f5b/resolve/main/adapter_model.bin
- Command line
-
hf download hf://dimasik1987/e30049b5-cd04-4fe0-b118-8281e9846f5b/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/dimasik1987/e30049b5-cd04-4fe0-b118-8281e9846f5b/resolve/main/adapter_model.bin
32.6 kB
- Xet hash:
- ab2530a298fb30ea4b1f6f5a4865a0fe9ea7d9c3c468a87c00105b471a026d0f
- Size of remote file:
- 32.6 kB
- SHA256:
- 2cde1b8d5eba5015866cf80d6f1335d95fbe46d86972eca0207e369f6a60b4d3
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