Instructions to use CognitiveLab/Ambari-One-Thrid-PEFT_final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CognitiveLab/Ambari-One-Thrid-PEFT_final with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-7b-hf") model = PeftModel.from_pretrained(base_model, "CognitiveLab/Ambari-One-Thrid-PEFT_final") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-712/optimizer.pt from CognitiveLab/Ambari-One-Thrid-PEFT_final: direct link, hf CLI and curl.
- Browser
- Download file 1.28 GB
-
https://huggingface.co/CognitiveLab/Ambari-One-Thrid-PEFT_final/resolve/main/checkpoint-712/optimizer.pt
- Command line
-
hf download hf://CognitiveLab/Ambari-One-Thrid-PEFT_final/checkpoint-712/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/CognitiveLab/Ambari-One-Thrid-PEFT_final/resolve/main/checkpoint-712/optimizer.pt
1.28 GB
- Xet hash:
- d2b819384a8f23c294afb539c759d5f4cd5cbf48e9277cb90d6ce83c494bf95b
- Size of remote file:
- 1.28 GB
- SHA256:
- d9577628b036b9664397157482a1ef4cabaa66e7af815b50694cbf86f00a4010
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