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 training_args.bin from havinash-ai/377d8250-51d3-4829-b83f-26d1ea9dfb50: direct link, hf CLI and curl.
- Browser
- Download file 6.78 kB
-
https://huggingface.co/havinash-ai/377d8250-51d3-4829-b83f-26d1ea9dfb50/resolve/8668f09249a52e871ce35d2dcf319b6fc0f7b4a9/training_args.bin
- Command line
-
hf download hf://havinash-ai/377d8250-51d3-4829-b83f-26d1ea9dfb50@8668f09249a52e871ce35d2dcf319b6fc0f7b4a9/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/havinash-ai/377d8250-51d3-4829-b83f-26d1ea9dfb50/resolve/8668f09249a52e871ce35d2dcf319b6fc0f7b4a9/training_args.bin
6.78 kB
- Xet hash:
- 9c17693d461d0f41f9bc1fab03386d367fe66c6401cd5b6ad35d8f5f2c3808d6
- Size of remote file:
- 6.78 kB
- SHA256:
- 23bb3b7adb55b0c6f33ef479dd080267d20f4b2cadf16b342cf8dc971967ca2f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.