Instructions to use TheMindExpansionNetwork/MindBot-Qwen3.8-27B-Synergetic-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use TheMindExpansionNetwork/MindBot-Qwen3.8-27B-Synergetic-LoRA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/m/model") model = PeftModel.from_pretrained(base_model, "TheMindExpansionNetwork/MindBot-Qwen3.8-27B-Synergetic-LoRA") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use TheMindExpansionNetwork/MindBot-Qwen3.8-27B-Synergetic-LoRA 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 TheMindExpansionNetwork/MindBot-Qwen3.8-27B-Synergetic-LoRA 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 TheMindExpansionNetwork/MindBot-Qwen3.8-27B-Synergetic-LoRA to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for TheMindExpansionNetwork/MindBot-Qwen3.8-27B-Synergetic-LoRA to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="TheMindExpansionNetwork/MindBot-Qwen3.8-27B-Synergetic-LoRA", 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 TheMindExpansionNetwork/MindBot-Qwen3.8-27B-Synergetic-LoRA to start chattingUsing HuggingFace Spaces for Unsloth
# No setup required# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for TheMindExpansionNetwork/MindBot-Qwen3.8-27B-Synergetic-LoRA to start chattingLoad model with FastModel
pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
model_name="TheMindExpansionNetwork/MindBot-Qwen3.8-27B-Synergetic-LoRA",
max_seq_length=2048,
)Quick Links
MindBot × Qwen3.8-27B Synergetic — LoRA Adapter
The council thinks out loud. A Qwen3.8-27B fine-tune that reasons step-by-step inside a
<start_working_out> block and delivers boxed <SOLUTION> answers — the MindBot persona for
the Mind Expansion Network's autonomous agents.
- 4-bit QLoRA · r=16, α=32 · targets: q/k/v/o + gate/up/down
- Data:
mindbot-synergetic-v1— 9,591 train / 533 val / 533 test / 17 held-out gold seeds - Shipped checkpoint: step 400 — train loss 0.0422, eval loss 0.0409 (no memorization gap)
- Base:
unsloth/Qwen3.8-27B(qwen3_5 hybrid linear+full attention, apache-2.0) - Trained with our unsloth fork on 1× A100-80GB (Modal)
Use
from unsloth import FastLanguageModel
model, tokenizer = FastLanguageModel.from_pretrained(
model_name="unsloth/Qwen3.8-27B", load_in_4bit=True)
model.load_adapter("TheMindExpansionNetwork/MindBot-Qwen3.8-27B-Synergetic-LoRA")
FastLanguageModel.for_inference(model)
Related
- GGUF quants: MindBot-Qwen3.8-27B-Synergetic-GGUF
- Full writeup: see the pinned discussion on this repo
- Pipeline repo: github.com/TheMindExpansionNetwork/mindbot-qwen38-train
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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 TheMindExpansionNetwork/MindBot-Qwen3.8-27B-Synergetic-LoRA to start chatting