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Meerkat-TRIZ-v1-Qwen3.8-27B
Meerkat-AI/Meerkat-TRIZ-v1-Qwen3.8-27B
Meerkat-TRIZ-v1-Qwen3.8-27B is a machine learning model from Meerkat-AI. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as apache-2.0.
LoRA adapter fine-tuned on TRIZ innovation methodology dataset.
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At a glance
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Aug 19, 2026
- Updated
- Aug 19, 2026
- SHA
- c7e8fda4
Base models
Model card
From the Hugging Face model README
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: q_proj, k_proj, v_proj, o_proj, in_proj_qkv, in_proj_z, in_proj_b, in_proj_a, out_proj, gate_proj, up_proj, down_proj
- 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
- Library
- peft
- License
- apache-2.0
- Created
- Aug 19, 2026
- Updated
- Aug 19, 2026