Instructions to use fieldvalley-llm2025/llm2025_main_rev2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use fieldvalley-llm2025/llm2025_main_rev2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "fieldvalley-llm2025/llm2025_main_rev2") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use fieldvalley-llm2025/llm2025_main_rev2 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
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 fieldvalley-llm2025/llm2025_main_rev2 to start chatting
Install Unsloth Studio (Windows)
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 fieldvalley-llm2025/llm2025_main_rev2 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for fieldvalley-llm2025/llm2025_main_rev2 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="fieldvalley-llm2025/llm2025_main_rev2", max_seq_length=2048, )
llm2025_main_rev2
This is a LoRA adapter fine-tuned on structured output tasks (REV2 SFT). It focuses on extracting pure Output only, removing CoT/Reasoning/Approach.
Base Model
Qwen/Qwen3-4B-Instruct-2507
Training Data
- u-10bei/structured_data_with_cot_dataset_512_v4
- daichira/structured-hard-sft-4k
Method
- Output-only extraction (Robust Regex Filtering)
- Fence stripping
- Unsloth optimized training
- Downloads last month
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Inference Providers NEW
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Model tree for fieldvalley-llm2025/llm2025_main_rev2
Base model
Qwen/Qwen3-4B-Instruct-2507