A fine-tuned Qwen 2.5 model, tuned for generating conversation titles and tags. This model is a fine-tuned version of Qwen/Qwen2.5-0.5B-Instruct using the Unsloth framework with LoRA (Low-Rank Adaptation) for efficient training. — Developed by: theprint — Model type: Causal Language Model (Fine-tuned with LoRA) — Language: en — License: apache-2.0 — Base model: Qwen/Qwen2.5-0.5B-Instruct — Fine-tuning method: LoRA with rank 128 Quantized GGUF versions are available in the theprint/TiTan-Qwen2.5-0.5B-GGUF repo. — TiTan-Qwen2.5-0.5B-f16.gguf (948.1 MB) — 16-bit float (original precision, largest file) — TiTan-Qwen2.5-0.5B-q3km.gguf (339.0 MB) — 3-bit quantization (medium quality) — TiTan-Qwen2.5-0.5B-q4km.gguf (379.4 MB) — 4-bit quantization (medium, recommended for most use cases) — TiTan-Qwen2.5-0.5B-q5km.gguf (400.6 MB) — 5-bit quantization (medium, good quality) — TiTan-Qwen2.5-0.5B-q6k.gguf (482.3 MB) — 6-bit quantization (high quality) — TiTan-Qwen2.5-0.5B-q80.gguf (506.5 MB) — — Training epochs: 2 — LoRA rank: 128 — Learning rate: 0.0001 — Batch…
Модальности:
Генерация текста
Области применения:
Диалог / чат
Задача: Генерация текста
Автор: theprint
Теги: peft, qwen2, lora, sft, trl, unsloth, fine-tuned, conversational
Лайков: 4 | Загрузок: 0
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
