1.9 KiB
pipeline_tag, inference, license, library_name, tags, base_model
| pipeline_tag | inference | license | library_name | tags | base_model | ||||
|---|---|---|---|---|---|---|---|---|---|
| text-generation | false | apache-2.0 | transformers |
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Note
This repository contains models that have been converted to the GGUF format with various quantizations from an IBM Granite base model.
Please reference the base model's full model card here: https://huggingface.co/ibm-granite/granite-4.0-tiny-preview
Granite-4.0-Tiny-Preview
Model Summary: 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.
- Developers: Granite Team, IBM
- Website: Granite Docs
- Release Date: May 2nd, 2025
- License: Apache 2.0
Supported Languages: 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.
Intended Use: This model is designed to handle general instruction-following tasks and can be integrated into AI assistants across various domains, including business applications.
Capabilities
- Thinking
- Summarization
- Text classification
- Text extraction
- Question-answering
- Retrieval Augmented Generation (RAG)
- Code related tasks
- Function-calling tasks
- Multilingual dialog use cases
- Long-context tasks including long document/meeting summarization, long document QA, etc.