ermiaazarkhalili/VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF - Каталог нейросетей
Генерация текста

ermiaazarkhalili/VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF

Добавлено:

GGUF quantizations of a LoRA fine-tune of WeiboAI/VibeThinker-3B, supervised fine-tuned on ermiaazarkhalili/claude-reasoning-distillation (private) (config sft). Quantized from ermiaazarkhalili/VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth. 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/sftdistillationvibethinker-3bunsloth.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:
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Задача: Генерация текста
Автор: ermiaazarkhalili
Теги: gguf, llama.cpp, quantized, unsloth, lora, trl, sft, endpoints_compatible
Лайков: 3  |  Загрузок: 319

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