Text Generation
PEFT
Safetensors
English
gemma
gemma2
lora
qlora
ai-safety
alignment
epistemology
instrument-trap
fine-tuned
scale-maximum
conversational
Instructions to use LumenSyntax/logos21-gemma2-27b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use LumenSyntax/logos21-gemma2-27b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2-27b-it-bnb-4bit") model = PeftModel.from_pretrained(base_model, "LumenSyntax/logos21-gemma2-27b") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model": "logos21-gemma2-27b", | |
| "base_model": "google/gemma-2-27b-it", | |
| "base_model_quantized": "unsloth/gemma-2-27b-it-bnb-4bit", | |
| "method": "QLoRA (4-bit NF4 + LoRA)", | |
| "framework": "unsloth", | |
| "lora_rank": 64, | |
| "lora_alpha": 64, | |
| "lora_target_modules": [ | |
| "q_proj", | |
| "k_proj", | |
| "v_proj", | |
| "o_proj", | |
| "gate_proj", | |
| "up_proj", | |
| "down_proj" | |
| ], | |
| "epochs": 3, | |
| "effective_batch_size": 8, | |
| "learning_rate": 0.0002, | |
| "lr_scheduler": "cosine", | |
| "max_seq_length": 2048, | |
| "dataset": "logos_gemma2_27b_nothink.jsonl", | |
| "dataset_size": 860, | |
| "dataset_composition": { | |
| "core_israel_protocol": 635, | |
| "meta_pattern": 45, | |
| "domain_transfer": 155, | |
| "ka_gap_targeting": 25 | |
| }, | |
| "train_on_responses_only": true, | |
| "think_blocks": "stripped (no-think variant)", | |
| "final_loss": 0.8026918817978398, | |
| "runtime_seconds": 1335.9304 | |
| } |