Instructions to use havinash-ai/377d8250-51d3-4829-b83f-26d1ea9dfb50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use havinash-ai/377d8250-51d3-4829-b83f-26d1ea9dfb50 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-128k-instruct") model = PeftModel.from_pretrained(base_model, "havinash-ai/377d8250-51d3-4829-b83f-26d1ea9dfb50") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from havinash-ai/377d8250-51d3-4829-b83f-26d1ea9dfb50: direct link, hf CLI and curl.
- Browser
- Download file 50.4 MB
-
https://huggingface.co/havinash-ai/377d8250-51d3-4829-b83f-26d1ea9dfb50/resolve/main/adapter_model.bin
- Command line
-
hf download hf://havinash-ai/377d8250-51d3-4829-b83f-26d1ea9dfb50/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/havinash-ai/377d8250-51d3-4829-b83f-26d1ea9dfb50/resolve/main/adapter_model.bin
50.4 MB
- Xet hash:
- 2fc48e8ad62945e9ea619bdc949e2d8cc5ec7ada6dfed04662dd1baa31937840
- Size of remote file:
- 50.4 MB
- SHA256:
- c229bc00e0ae7c42eea282f97a68afc119ca4079aa8805c74c478e44251104d7
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