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Granite 4.0 Tiny Preview

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.

Parameter Sizes

7B:

NOTE: This is the draft name!

ollama run gabegoodhart/granite4-preview:tiny

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.

Evaluation Results

Comparison with previous granite models1. Scores of AlpacaEval-2.0 and Arena-Hard are calculated with thinking=True
Models Arena-Hard AlpacaEval-2.0 MMLU PopQA TruthfulQA BigBenchHard DROP GSM8K HumanEval HumanEval+ IFEval AttaQ
Granite-3.3-2B-Instruct 28.86 43.45 55.88 18.4 58.97 52.51 35.98 72.48 80.51 75.68 65.8 87.47
Granite-3.3-8B-Instruct 57.56 62.68 65.54 26.17 66.86 59.01 41.53 80.89 89.73 86.09 74.82 88.5
Granite-4.0-Tiny-Preview 26.70 35.16 60.40 22.93 58.07 55.71 46.22 70.05 82.41 78.33 63.03 86.10

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