Instructions to use JesseLiu/llama32_ReMeDi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use JesseLiu/llama32_ReMeDi with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-3B-Instruct") model = PeftModel.from_pretrained(base_model, "JesseLiu/llama32_ReMeDi") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from JesseLiu/llama32_ReMeDi: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/JesseLiu/llama32_ReMeDi/resolve/main/tokenizer.json
- Command line
-
hf download hf://JesseLiu/llama32_ReMeDi/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/JesseLiu/llama32_ReMeDi/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- 9c6ccb0740c1d182fa4f7c65f0d78dd1b9e17fb3cafb19b86761385982fa2d06
- Size of remote file:
- 17.2 MB
- SHA256:
- 384a7e7c676f7be2e5d2e8449c508be9b00e5b18c5b3c39ebc626e96b3f4b988
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