Instructions to use AlignmentResearch/hr_sdf_exclude_Llama-3.1-8B-Instruct_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use AlignmentResearch/hr_sdf_exclude_Llama-3.1-8B-Instruct_v1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.1-8B-Instruct") model = PeftModel.from_pretrained(base_model, "AlignmentResearch/hr_sdf_exclude_Llama-3.1-8B-Instruct_v1") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from AlignmentResearch/hr_sdf_exclude_Llama-3.1-8B-Instruct_v1: direct link, hf CLI and curl.
- Browser
- Download file 17.2 MB
-
https://huggingface.co/AlignmentResearch/hr_sdf_exclude_Llama-3.1-8B-Instruct_v1/resolve/main/tokenizer.json
- Command line
-
hf download hf://AlignmentResearch/hr_sdf_exclude_Llama-3.1-8B-Instruct_v1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/AlignmentResearch/hr_sdf_exclude_Llama-3.1-8B-Instruct_v1/resolve/main/tokenizer.json
17.2 MB
- Xet hash:
- dcf82f79366ffaa42765bb85659d9f32f401dc0a70a9c23e7fc2707ee5cdfc94
- Size of remote file:
- 17.2 MB
- SHA256:
- 051830f2f6c06d23b79bfeb1cb00c36ab32a29c2905e80e0b8e22148b654ec8b
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