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Model: ibm-granite/granite-4.0-tiny-preview-GGUF Source: Original Platform
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README.md
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README.md
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pipeline_tag: text-generation
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inference: false
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license: apache-2.0
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library_name: transformers
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tags:
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- language
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- granite-4.0
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- gguf
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base_model:
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- ibm-granite/granite-4.0-tiny-base-preview
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---
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> [!NOTE]
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> This repository contains models that have been converted to the GGUF format with various quantizations from an IBM Granite base model.
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>
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> Please reference the base model's full model card here:
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> https://huggingface.co/ibm-granite/granite-4.0-tiny-preview
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# Granite-4.0-Tiny-Preview
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**Model Summary:**
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Granite-4-Tiny-Preview is a 7B parameter fine-grained hybrid mixture-of-experts (MoE) instruct model fine-tuned from Granite-4.0-Tiny-Base-Preview using a combination of open source instruction datasets with permissive license and internally collected synthetic datasets tailored for solving long context problems. This model is developed using a diverse set of techniques with a structured chat format, including supervised fine-tuning, and model alignment using reinforcement learning.
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- **Developers:** Granite Team, IBM
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- **Website**: [Granite Docs](https://www.ibm.com/granite/docs/)
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- **Release Date**: May 2nd, 2025
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- **License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0)
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**Supported Languages:**
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English, German, Spanish, French, Japanese, Portuguese, Arabic, Czech, Italian, Korean, Dutch, and Chinese. However, users may fine-tune this Granite model for languages beyond these 12 languages.
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**Intended Use:**
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This model is designed to handle general instruction-following tasks and can be integrated into AI assistants across various domains, including business applications.
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**Capabilities**
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* Thinking
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* Summarization
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* Text classification
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* Text extraction
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* Question-answering
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* Retrieval Augmented Generation (RAG)
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* Code related tasks
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* Function-calling tasks
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* Multilingual dialog use cases
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* Long-context tasks including long document/meeting summarization, long document QA, etc.
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