MetaphoricalCode/Qwen3-Gutenberg-Encore-14B-exl3-4bpw-hb6

Quantized using the default exllamav3 (0.0.3) quantization process.

• Original model: https://huggingface.co/nbeerbower/Qwen3-Gutenberg-Encore-14B
• exllamav3: https://github.com/turboderp-org/exllamav3

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Qwen3-Gutenberg-Encore-14B

nbeerbower/Xiaolong-Qwen3-14B finetuned on:

• jondurbin/gutenberg-dpo-v0.1
• nbeerbower/gutenberg2-dpo
• nbeerbower/gutenberg-moderne-dpo
• nbeerbower/synthetic-fiction-dpo
• nbeerbower/Arkhaios-DPO
• nbeerbower/Purpura-DPO
• nbeerbower/Schule-DPO

Method

ORPO tuned with 1x RTX A6000 for 3 epochs.

QLoRA config

# QLoRA config
bnb_config = BitsAndBytesConfig(
    load_in_4bit=True,
    bnb_4bit_quant_type="nf4",
    bnb_4bit_compute_dtype=torch_dtype,
    bnb_4bit_use_double_quant=True,
)
# LoRA config
peft_config = LoraConfig(
    r=64,
    lora_alpha=128,
    lora_dropout=0.05,
    bias="none",
    task_type="CAUSAL_LM",
    target_modules=['up_proj', 'down_proj', 'gate_proj', 'k_proj', 'q_proj', 'v_proj', 'o_proj']
)

ORPO config

orpo_args = ORPOConfig(
    learning_rate=8e-6,
    lr_scheduler_type="cosine",
    warmup_ratio=0.05,
    max_length=4096,
    max_prompt_length=1024,
    max_completion_length=4096,
    beta=0.1,
    per_device_train_batch_size=1,
    per_device_eval_batch_size=1,
    gradient_accumulation_steps=64,
    optim="paged_adamw_8bit",
    num_train_epochs=3,
    max_grad_norm=0.5,
    bf16=True,
)