Painted Fantasy

PAINTED FANTASY v2

MS3.2-24B

Overview

This is an uncensored creative model intended to excel at character driven RP / ERP.

Version 2 feels quite different from the original, with a heavy focus on reducing repetition across conversations and improving instruction following.

Has a pretty unique writing style and sense of creativity (IMO). Pays the price with intermittent brain farts though.

SillyTavern Settings

Recommended Roleplay Format

> Actions: In plaintext > Dialogue: "In quotes" > Thoughts: *In asterisks*

Suggested Samplers

> Temp: 0.5-0.6 > MinP: 0.1 > TopP: 0.95 > Dry: 0.8, 1.75, 4

Instruct

Mistral v7 Tekken

Quantizations

GGUF

> Static (mradermacher) > iMatrix (mradermacher)

EXL3

> 3bpw > 3.5bpw > 4bpw > 5bpw > 6bpw

Training Process

Training process: SFT > DPO > KTO

SFT with RP/ERP, Stories and in character assistant data.

DPO focused on reducing repetition, misgendered characters and slop.

KTO focused on further reducing repetition and slop.

> Axolotl configs

Not optimized for cost / performance efficiency, YMMV.

SFT 1*H100

# ====================
# MODEL CONFIGURATION
# ====================
base_model: ConicCat/Mistral-Small-3.2-AntiRep-24B
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
chat_template: mistral_v7_tekken


# ====================
# DATASET CONFIGURATION
# ====================
datasets:
  - path: ./dataset.jsonl
    type: chat_template
    split: train
    chat_template_strategy: tokenizer
    field_messages: messages
    message_property_mappings:
      role: role
      content: content
    roles:
      user: ["user"]
      assistant: ["assistant"]
      system: ["system"]dataset_prepared_path:
train_on_inputs: false  # Only train on assistant responses
# ====================
# QLORA CONFIGURATION
# ====================
adapter: qlora
load_in_4bit: true
lora_r: 128
lora_alpha: 128
lora_dropout: 0.1
lora_target_linear: true
# lora_modules_to_save:  # Uncomment only if you added NEW tokens
# ====================
# TRAINING PARAMETERS
# ====================
num_epochs: 3
micro_batch_size: 8
gradient_accumulation_steps: 1
learning_rate: 1e-5
optimizer: paged_adamw_8bit
lr_scheduler: rex
warmup_ratio: 0.05
weight_decay: 0.01
max_grad_norm: 1.0
# ====================
# SEQUENCE & PACKING
# ====================
sequence_len: 8192
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true
# ====================
# HARDWARE OPTIMIZATIONS
# ====================
bf16: auto
flash_attention: true
gradient_checkpointing: true
# ====================
# EVALUATION & CHECKPOINTING
# ====================
save_strategy: steps
save_steps: 20
save_total_limit: 5  # Keep best + last few checkpoints
load_best_model_at_end: true
metric_for_best_model: eval_loss
greater_is_better: false
# ====================
# LOGGING & OUTPUT
# ====================
output_dir: ./PT-SFT_1
logging_steps: 2
save_safetensors: true
# ====================
# WANDB TRACKING
# ====================
wandb_project: PF-SFT
wandb_entity: your_entity
wandb_name: run_name

zerofata/MS3.2-PaintedFantasy-v2-24b-exl3-5bpw