Phi-3-mini-4k-instruct-gguf

モデル紹介

This repo provides the GGUF format for the Phi-3-Mini-4K-Instruct. The Phi-3-Mini-4K-Instruct is a 3.8B parameters, lightweight, state-of-the-art open model trained with the Phi-3 datasets that includes both synthetic data and the filtered publicly available websites data with a focus on high-quality and reasoning dense properties. The model belongs to the Phi-3 family with the Mini version in two variants 4K and 128K which is the context length (in tokens) it can support. The model has underwent a post-training process that incorporates both supervised fine-tuning and direct preference optimization to ensure precise instruction adherence and robust safety measures. When assessed against benchmarks testing common sense, language understanding, math, code, long context and logical reasoning, Phi-3 Mini-4K-Instruct showcased a robust and state-of-the-art performance among models with less than 13 billion parameters. + Phi-3 Microsoft Blog + Phi-3 Technical Report + Phi-3 on Azure AI Studio + Phi-3 on Hugging Face + Phi-3 ONNX: 4K and 128K This repo provides GGUF files for the Phi-3 Mini-4K-Instruct model. | Name | Quant method | Bits | Size | Use case | | ---- | ---- | ---- | ---- | ----- | | Phi-3-mini-4k-instruct-q4.gguf | Q4_K_M | 4 | 2.2 GB| medium, balanced quality - recommended | | Phi-3-mini-4k-instruct-fp16.gguf | None | 16 | 7.2 GB | minimal quality loss |

主な特徴

特点摘要待依据来源补齐，不凭模型名称推断能力。

制約と注意点

具体的な制約を判断する出典が不足しています。実際の性能、遅延、データ方針、ライセンス、提供期間を確認してください。

出典別料金と費用分析

料金はチャネル・地域・設定によって異なります。各チャネルの料金は個別に表示し、提供元の統一公式料金とは見なしません。

公開評価と実行設定

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

よくある質問

出典と追跡記録

许可证：mit。模型介绍与第三方评测均以原来源的具体版本和方法为准。