Instructions to use VictorDCh/Llama-3-8B-Instruct-MoE-2-spider with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use VictorDCh/Llama-3-8B-Instruct-MoE-2-spider with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("VictorDCh/Llama-3-8B-Instruct-MoE-2") model = PeftModel.from_pretrained(base_model, "VictorDCh/Llama-3-8B-Instruct-MoE-2-spider") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from VictorDCh/Llama-3-8B-Instruct-MoE-2-spider: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/VictorDCh/Llama-3-8B-Instruct-MoE-2-spider/resolve/main/training_args.bin
- Command line
-
hf download hf://VictorDCh/Llama-3-8B-Instruct-MoE-2-spider/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/VictorDCh/Llama-3-8B-Instruct-MoE-2-spider/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 490ab0c0d46c7b767b88cd9019afb7807350691dcfec638660c92d40ff5b6a0f
- Size of remote file:
- 4.73 kB
- SHA256:
- 03675dba26f34eba4d2bad743347e9738d4898201ad8bf7c6bcc17a51469ae43
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