Qwen 2.5 Math 14B Iter 2
Collection
Qwen 2.5 is missing it's 14B and 32B math variants!! I have taken it upon myself to create them :) These are the Iteration 2 Models • 3 items • Updated • 1
How to use qingy2024/Qwen2.5-14B-Math-LoRA-Iter2 with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("qingy2024/Qwen2.5-14B-Math-LoRA-Iter2", dtype="auto")How to use qingy2024/Qwen2.5-14B-Math-LoRA-Iter2 with Unsloth Studio:
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for qingy2024/Qwen2.5-14B-Math-LoRA-Iter2 to start chatting
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for qingy2024/Qwen2.5-14B-Math-LoRA-Iter2 to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for qingy2024/Qwen2.5-14B-Math-LoRA-Iter2 to start chatting
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="qingy2024/Qwen2.5-14B-Math-LoRA-Iter2",
max_seq_length=2048,
)Huge thanks to Unsloth and the Huggingface TRL library.
This model is Qwen 2.5 14B fine tuned for a full epoch on the high quality garage-bAInd/Open-Platypus dataset for STEM reasoning.
| Training Detail | Value |
|---|---|
| Epochs | 1 |
| Steps | 2077 |
| Loss | 0.4218 |
| Batch size | 4 |
| Gradient Acc. Steps | 3 |
| Learning Rate | 2e-4 |
| LR Scheduler | cosine |
| Rank | 32 |
| Rank-Stabilized LoRA | Yes |
| Warm up steps | 5 |
| Weight Decay | 0.01 |
| Seed | 3407 |