Instructions to use CrystalRaindropsFall/smollm2-gsm8k-curriculum-complexity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CrystalRaindropsFall/smollm2-gsm8k-curriculum-complexity with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("experiment_results/curriculum_complexity_score_smolLM2_gsm8k_20251112_222922/stage_2_normal/merged_model") model = PeftModel.from_pretrained(base_model, "CrystalRaindropsFall/smollm2-gsm8k-curriculum-complexity") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from CrystalRaindropsFall/smollm2-gsm8k-curriculum-complexity: direct link, hf CLI and curl.
- Browser
- Download file 5.94 kB
-
https://huggingface.co/CrystalRaindropsFall/smollm2-gsm8k-curriculum-complexity/resolve/main/training_args.bin
- Command line
-
hf download hf://CrystalRaindropsFall/smollm2-gsm8k-curriculum-complexity/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CrystalRaindropsFall/smollm2-gsm8k-curriculum-complexity/resolve/main/training_args.bin
5.94 kB
- Xet hash:
- 774bb4c374a6a9df01fcbcedaf1cb6a283003aec08a36cf4dbeeb991e749c9d6
- Size of remote file:
- 5.94 kB
- SHA256:
- ebe69044be4b205a2fb5fbf1482e23a773dc62ff6a19e21c93d1424c639e56ce
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.