Instructions to use dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("scb10x/llama-3-typhoon-v1.5-8b-instruct") model = PeftModel.from_pretrained(base_model, "dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.safetensors from dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e: direct link, hf CLI and curl.
- Browser
- Download file 336 MB
-
https://huggingface.co/dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/dada22231/75e85b72-6648-49d6-9f3e-75d68ddfd43e/resolve/main/adapter_model.safetensors
336 MB
- Xet hash:
- cbae9e8267758378fc244b7fcb685b271cf3dcb01e6bfeab7d8a4c7abd95dbcd
- Size of remote file:
- 336 MB
- SHA256:
- f1e9ce52cba4d77aeaff2bdc865a6eb43d6562b1b36bf175216777d25df00d96
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