Instructions to use fieldvalley-llm2025/main_rev2_sft04 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use fieldvalley-llm2025/main_rev2_sft04 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/main_rev2_sft04") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use fieldvalley-llm2025/main_rev2_sft04 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/main_rev2_sft04 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/main_rev2_sft04 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/main_rev2_sft04 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="fieldvalley-llm2025/main_rev2_sft04", max_seq_length=2048, )
Upload README.md with huggingface_hub
Browse files
README.md
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base_model:
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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#
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- **
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- **Finetuned from model :** unsloth/qwen3-4b-instruct-2507-unsloth-bnb-4bit
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base_model: Qwen/Qwen3-4B-Instruct-2507
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library_name: peft
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license: other
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tags:
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- unsloth
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- lora
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- sft
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- completion-only
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- struct-eval
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- hard-filter
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model-index:
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- name: main_rev2_sft04
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results: []
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# main_rev2_sft04
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This is a **Safe SFT** LoRA adapter (REV2 SFT04).
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It uses **Completion-only Training** and **Hard SFT Filtering**.
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## Base Model
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Qwen/Qwen3-4B-Instruct-2507
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## Training Data (Mixed 65:35)
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- 65%: daichira/structured-hard-sft-4k (Filtered High Quality)
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- 35%: u-10bei/structured_data_with_cot_dataset_512_v4 (Filtered Output-only)
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## Hard Filter Applied
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- Length Limit (Format-wise)
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- Anti-Log/Audit Keywords
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- Repetition Check (Tokens, Lines, Gases)
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## Method
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- **Completion-only**: User prompts are masked (-100 output label).
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- **Marker**: `
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### OUTPUT
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` inserted before assistant output.
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- **Config**: 1 Epoch, Max Seq Length 4096.
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