metadata

base_model: ibm-granite/granite-3.0-8b-instruct
license: apache-2.0
pipeline_tag: text-generation
tags:
  - language
  - granite-3.0
quantized_model: AliNemati
inference: false
model-index:
  - name: granite-3.0-2b-instruct
    results:
      - task:
          type: text-generation
        dataset:
          name: IFEval
          type: instruction-following
        metrics:
          - type: pass@1
            value: 52.27
            name: pass@1
          - type: pass@1
            value: 8.22
            name: pass@1
      - task:
          type: text-generation
        dataset:
          name: AGI-Eval
          type: human-exams
        metrics:
          - type: pass@1
            value: 40.52
            name: pass@1
          - type: pass@1
            value: 65.82
            name: pass@1
          - type: pass@1
            value: 34.45
            name: pass@1
      - task:
          type: text-generation
        dataset:
          name: OBQA
          type: commonsense
        metrics:
          - type: pass@1
            value: 46.6
            name: pass@1
          - type: pass@1
            value: 71.21
            name: pass@1
          - type: pass@1
            value: 82.61
            name: pass@1
          - type: pass@1
            value: 77.51
            name: pass@1
          - type: pass@1
            value: 60.32
            name: pass@1
      - task:
          type: text-generation
        dataset:
          name: BoolQ
          type: reading-comprehension
        metrics:
          - type: pass@1
            value: 88.65
            name: pass@1
          - type: pass@1
            value: 21.58
            name: pass@1
      - task:
          type: text-generation
        dataset:
          name: ARC-C
          type: reasoning
        metrics:
          - type: pass@1
            value: 64.16
            name: pass@1
          - type: pass@1
            value: 33.81
            name: pass@1
          - type: pass@1
            value: 51.55
            name: pass@1
      - task:
          type: text-generation
        dataset:
          name: HumanEvalSynthesis
          type: code
        metrics:
          - type: pass@1
            value: 64.63
            name: pass@1
          - type: pass@1
            value: 57.16
            name: pass@1
          - type: pass@1
            value: 65.85
            name: pass@1
          - type: pass@1
            value: 49.6
            name: pass@1
      - task:
          type: text-generation
        dataset:
          name: GSM8K
          type: math
        metrics:
          - type: pass@1
            value: 68.99
            name: pass@1
          - type: pass@1
            value: 30.94
            name: pass@1
      - task:
          type: text-generation
        dataset:
          name: PAWS-X (7 langs)
          type: multilingual
        metrics:
          - type: pass@1
            value: 64.94
            name: pass@1
          - type: pass@1
            value: 48.2
            name: pass@1

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Model creator: ibm-granite

Original model: granite-3.0-3b-a800m-instruct

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Model Summary:

Granite-3.0-8B-Instruct is an 8B parameter model finetuned from Granite-3.0-8B-Base using a combination of open-source instruction datasets with permissive licenses 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.

Technical Specifications:

Granite-3.0-8B-Instruct

Model Summary: Granite-3.0-8B-Instruct is a 8B parameter model finetuned from Granite-3.0-8B-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.

Developers: Granite Team, IBM
GitHub Repository: ibm-granite/granite-3.0-language-models
Website: Granite Docs
Paper: Granite 3.0 Language Models
Release Date: October 21st, 2024
License: Apache 2.0

Supported Languages: English, German, Spanish, French, Japanese, Portuguese, Arabic, Czech, Italian, Korean, Dutch, and Chinese. Users may finetune Granite 3.0 models for languages beyond these 12 languages.

Intended use: The model is designed to respond to general instructions and can be used to build AI assistants for multiple domains, including business applications.

Capabilities

Summarization
Text classification
Text extraction
Question-answering
Retrieval Augmented Generation (RAG)
Code related tasks
Function-calling tasks
Multilingual dialog use cases

About osllm.ai:

osllm.ai is a community-driven platform that provides access to a wide range of open-source language models.

IndoxJudge: A free, open-source tool for evaluating large language models (LLMs).
It provides key metrics to assess performance, reliability, and risks like bias and toxicity, helping ensure model safety.
inDox: An open-source retrieval augmentation tool for extracting data from various
document formats (text, PDFs, HTML, Markdown, LaTeX). It handles structured and unstructured data and supports both
online and offline LLMs.
IndoxGen: A framework for generating high-fidelity synthetic data using LLMs and
human feedback, designed for enterprise use with high flexibility and precision.
Phoenix: A multi-platform, open-source chatbot that interacts with documents
locally, without internet or GPU. It integrates inDox and IndoxJudge to improve accuracy and prevent hallucinations,
ideal for sensitive fields like healthcare.
Phoenix_cli: A multi-platform command-line tool that runs LLaMA models locally,
supporting up to eight concurrent tasks through multithreading, eliminating the need for cloud-based services.

Special thanks

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