— Quantization method: AWQ — Bits: 4 — Group Size: 32 — Calibration Dataset: nvidia/Llama-Nemotron-Post-Training-Dataset — Quantization Tool: llm-compressor — The model can not load with tensor parallelism and pipeline parallelism. Model Summary: Granite-4.0-H-Tiny is a 7B parameter long-context instruct model finetuned from Granite-4.0-H-Tiny-Base using a combination of open source instruction datasets with permissive license and internally collected synthetic datasets. This model is developed using a diverse set of techniques with a structured chat format, including supervised finetuning, model alignment using reinforcement learning, and model merging. Granite 4.0 instruct models feature improved instruction following (IF) and tool-calling capabilities, making them more effective in enterprise applications. — Developers: Granite Team, IBM — HF Collection: Granite 4.0 Language Models HF Collection — GitHub Repository: ibm-granite/granite-4.0-language-models — Website: Granite Docs — Release Date: October 2nd, 2025 — License: Apache 2.0 Supported Languages: English, German, Spanish, French, Japanese, Portuguese, Arabic, Czech, Italian, Korean, Dutch, and Chinese. Users may…
Модальности:
Генерация текста
Области применения:
Диалог / чат
Задача: Генерация текста
Автор: cyankiwi
Теги: granitemoehybrid, language, granite-4.0, conversational, endpoints_compatible, compressed-tensors
Лайков: 3 | Загрузок: 95
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
