--- 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 --- **osllm.ai Models Highlights Program** **We believe there's no need to pay a token if you have a GPU on your computer.** Highlighting new and noteworthy models from the community. Join the conversation on Discord. **Model creator**: ibm-granite **Original model**: granite-3.0-3b-a800m-instruct

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Email: support@osllm.ai **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](https://github.com/ibm-granite/granite-3.0-language-models) - **Website**: [Granite Docs](https://www.ibm.com/granite/docs/) - **Paper:** [Granite 3.0 Language Models](https://github.com/ibm-granite/granite-3.0-language-models/blob/main/paper.pdf) - **Release Date**: October 21st, 2024 - **License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-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](https://osllm.ai)**: [osllm.ai](https://osllm.ai) is a community-driven platform that provides access to a wide range of open-source language models. 1. **[IndoxJudge](https://github.com/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. 1. **[inDox](https://github.com/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. 1. **[IndoxGen](https://github.com/IndoxGen)**: A framework for generating high-fidelity synthetic data using LLMs and human feedback, designed for enterprise use with high flexibility and precision. 1. **[Phoenix](https://github.com/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. 1. **[Phoenix_cli](https://github.com/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** 🙏 Special thanks to [**Georgi Gerganov**](https://github.com/ggerganov) and the whole team working on [**llama.cpp**](https://github.com/ggerganov/llama.cpp) for making all of this possible. **Disclaimers** [osllm.ai](https://osllm.ai) is not the creator, originator, or owner of any Model featured in the Community Model Program. Each Community Model is created and provided by third parties. osllm.ai does not endorse, support, represent, or guarantee the completeness, truthfulness, accuracy, or reliability of any Community Model. You understand that Community Models can produce content that might be offensive, harmful, inaccurate, or otherwise inappropriate, or deceptive. Each Community Model is the sole responsibility of the person or entity who originated such Model. osllm.ai may not monitor or control the Community Models and cannot, and does not, take responsibility for any such Model. osllm.ai disclaims all warranties or guarantees about the accuracy, reliability, or benefits of the Community Models. osllm.ai further disclaims any warranty that the Community Model will meet your requirements, be secure, uninterrupted, or available at any time or location, or error-free, virus-free, or that any errors will be corrected, or otherwise. You will be solely responsible for any damage resulting from your use of or access to the Community Models, your downloading of any Community Model, or use of any other Community Model provided by or through [osllm.ai](https://osllm.ai).