Instructions to use fieldvalley-llm2025/main_rev2_sft06 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use fieldvalley-llm2025/main_rev2_sft06 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_sft06") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use fieldvalley-llm2025/main_rev2_sft06 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_sft06 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_sft06 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_sft06 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_sft06", max_seq_length=2048, )
How to use from
Unsloth StudioInstall 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_sft06 to start chattingUsing HuggingFace Spaces for Unsloth
# No setup required# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for fieldvalley-llm2025/main_rev2_sft06 to start chattingLoad model with FastModel
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="fieldvalley-llm2025/main_rev2_sft06",
max_seq_length=2048,
)Quick Links
main_rev2_sft06
This is a Safe SFT LoRA adapter (REV2 SFT06). It uses Completion-only Training and Enhanced TOML Refinement Filter (Followup Patch).
Base Model
Qwen/Qwen3-4B-Instruct-2507
Training Data (Mixed 65:35, TOML <= 10%)
- 65%: daichira/structured-hard-sft-4k (Filtered + Refined TOML)
- 35%: u-10bei/structured_data_with_cot_dataset_512_v4 (Filtered + Refined TOML)
TOML Refinement Applied (Followup)
- Drop Audit/Log: Complete elimination of 'audit', 'timestamp', 'created by' (case-insensitive).
- Drop Repetition:
- Quoted String Repeat (>=12 times).
- Key Repeat ('mineral_name', etc).
- Inline Big Array (25+ elements).
Method
- Completion-only: User prompts are masked.
- Marker: `
OUTPUT
`.
- Config: 1 Epoch, Max Seq Length 4096.
- Downloads last month
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Model tree for fieldvalley-llm2025/main_rev2_sft06
Base model
Qwen/Qwen3-4B-Instruct-2507
Install Unsloth Studio (macOS, Linux, WSL)
# 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_sft06 to start chatting