Meerkat-AI/Meerkat-TRIZ-v1-Qwen3.8-27B
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Meerkat-TRIZ-v1 (Qwen3.8-27B)
LoRA adapter fine-tuned on TRIZ innovation methodology dataset.
Base Model
- Base: Qwen3.8-27B
- Architecture: Qwen3_5ForConditionalGeneration
- Precision: BF16
Adapter Config
- PEFT Type: LoRA
- Rank (r): 64
- Alpha: 128
- Dropout: 0.0
- Target Modules: qproj, kproj, vproj, oproj, inprojqkv, inprojz, inprojb, inproja, outproj, gateproj, upproj, downproj
- Trainable Params: 466,911,232 (1.7064% of base)
Training
- Framework: TRL SFTTrainer
- Dataset: v5a (11,096 train / 1,050 val)
- Max Length: 2048
- Horizon: 2,774 steps (cosine decay)
- Best Eval Loss: 1.505834 @ step 1300
- Early Stopping: patience=3, threshold=0.002
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.8-27B", torch_dtype="auto", device_map="auto")
model = PeftModel.from_pretrained(base, "Meerkat-AI/Meerkat-TRIZ-v1-Qwen3.8-27B")
tokenizer = AutoTokenizer.from_pretrained("Meerkat-AI/Meerkat-TRIZ-v1-Qwen3.8-27B")Related Models
- Meerkat-TRIZ-v1-Qwen3.6-35B-A3B ← Original v1 (older base)
- Meerkat-TRIZ Collection ← All variants
