GGUF quantizations of a LoRA fine-tune of empero-ai/Qwen3.8-9B, supervised fine-tuned on ermiaazarkhalili/Fable-5-Glint-Clean (private). Quantized from ermiaazarkhalili/Qwen3.8-9B-SFT-Fable5-Glint. See that repository for the full-precision weights. Measured from our SLURM logs for this configuration. These are training-loss observations only — no downstream benchmark evaluation has been run on this model, so they should not be read as a quality claim. — No benchmark evaluation has been run on this checkpoint. The only reported numbers are training-loss observations. — Inherits the biases, knowledge cutoff and failure modes of the base model. — Fine-tuned on a single instruction-following dataset; behaviour outside that distribution is untested. — LoRA adapters were merged into the base weights, so the merged model cannot be detached from this fine-tune. Trained by notebooks/fabledistillationqwen38-9bfable-glintunsloth.ipynb, executed non-interactively with papermill on a SLURM H100 partition (Unsloth + TRL, LoRA). Card generated from the training run’s own configuration and logs by scripts/generatehubmodelcard.py.
Модальности:
Генерация текста
Области применения:
Диалог / чат
Задача: Генерация текста
Автор: ermiaazarkhalili
Теги: gguf, llama.cpp, quantized, unsloth, lora, trl, sft, endpoints_compatible
Лайков: 3 | Загрузок: 365
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
