Instructions to use msho/dspv1_sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use msho/dspv1_sft with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("deepseek-ai/DeepSeek-Prover-V1") model = PeftModel.from_pretrained(base_model, "msho/dspv1_sft") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from msho/dspv1_sft: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/msho/dspv1_sft/resolve/main/training_args.bin
- Command line
-
hf download hf://msho/dspv1_sft/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/msho/dspv1_sft/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- 8e46d8f8bf4ca162fc7581a56997e164ab09cae7ce9c4a409576089f162e0b62
- Size of remote file:
- 5.43 kB
- SHA256:
- 458128a3d0228cd28f5f2453d2307498515638fbe87ff58d2ba6eb286d94e993
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.