Instructions to use Chi0715/DeepSeek-GRPO-output-checkpoint-250 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Chi0715/DeepSeek-GRPO-output-checkpoint-250 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("deepseek-ai/DeepSeek-R1-Distill-Qwen-14B") model = PeftModel.from_pretrained(base_model, "Chi0715/DeepSeek-GRPO-output-checkpoint-250") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Chi0715/DeepSeek-GRPO-output-checkpoint-250: direct link, hf CLI and curl.
- Browser
- Download file 5.75 kB
-
https://huggingface.co/Chi0715/DeepSeek-GRPO-output-checkpoint-250/resolve/main/training_args.bin
- Command line
-
hf download hf://Chi0715/DeepSeek-GRPO-output-checkpoint-250/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Chi0715/DeepSeek-GRPO-output-checkpoint-250/resolve/main/training_args.bin
5.75 kB
- Xet hash:
- b7ff9d137643fae538037e299e65822082a1a13463eaf7cf07c5cdb492d82359
- Size of remote file:
- 5.75 kB
- SHA256:
- 08c7e6d65b45d5640a03a7264f5a07a6d8ee9bc4936fc268966f6f37df57c090
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.