Instructions to use fedovtt/3d2de059-3399-4eb1-bda5-1d099c0e49c1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use fedovtt/3d2de059-3399-4eb1-bda5-1d099c0e49c1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM-135M-Instruct") model = PeftModel.from_pretrained(base_model, "fedovtt/3d2de059-3399-4eb1-bda5-1d099c0e49c1") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from fedovtt/3d2de059-3399-4eb1-bda5-1d099c0e49c1: direct link, hf CLI and curl.
- Browser
- Download file 6.71 kB
-
https://huggingface.co/fedovtt/3d2de059-3399-4eb1-bda5-1d099c0e49c1/resolve/main/training_args.bin
- Command line
-
hf download hf://fedovtt/3d2de059-3399-4eb1-bda5-1d099c0e49c1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/fedovtt/3d2de059-3399-4eb1-bda5-1d099c0e49c1/resolve/main/training_args.bin
6.71 kB
- Xet hash:
- d457a48800c8855030d5c5c34028ed7122075c5e1a3636e485c5f06cb05ad931
- Size of remote file:
- 6.71 kB
- SHA256:
- 1ee2da36e9c02ba59240e80b38ed9031f5dd69487fd5df5788e4cd509c424df8
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