command-r7b:7b-12-2024-fp16

C4AI Command R7B 是 7B 參數模型的開放權重研究版本，具有先進的功能，針對各種用例進行了最佳化，包括推理、摘要、問答和程式碼。該模型經過訓練，可以執行複雜的任務，包括檢索增強生成 (RAG) 和工具使用。該模型還具有強大的代理能力，能夠使用和組合多種工具，透過多個步驟來完成更困難的任務。它在企業相關的程式碼用例中獲得了頂級效能。C4AI Command R7B 是一個使用 23 種語言訓練的多語言模型。

模型詳細資訊

模型架構： 這是一個自迴歸語言模型，使用最佳化的 Transformer 架構。在預訓練之後，此模型使用監督式微調 (SFT) 和偏好訓練，以使模型行為與人類對於有幫助和安全的偏好保持一致。該模型具有三層滑動視窗注意力（視窗大小 4096）和 ROPE，用於高效的本地上下文建模和相對位置編碼。第四層使用全局注意力，不帶位置嵌入，從而實現整個序列中不受限制的 Token 互動。

涵蓋語言： 該模型已使用 23 種語言進行訓練：English, French, Spanish, Italian, German, Portuguese, Japanese, Korean, Arabic, Chinese, Russian, Polish, Turkish, Vietnamese, Dutch, Czech, Indonesian, Ukrainian, Romanian, Greek, Hindi, Hebrew, 和 Persian。

> Note: this model requires [Ollama 0.5.5](https://github.com/ollama/ollama/releases/tag/v0.5.5)

![r7b.jpg](/assets/library/command-r7b/709a1bd1-3f55-4e90-b3ca-40db45e13683)

C4AI Command R7B is an open weights research release of a 7B billion parameter model with advanced capabilities optimized for a variety of use cases including reasoning, summarization, question answering, and code. The model is trained to perform sophisticated tasks including Retrieval Augmented Generation (RAG) and tool use. The model also has powerful agentic capabilities with the ability to use and combine multiple tools over multiple steps to accomplish more difficult tasks. It obtains top performance on enterprise relevant code use cases. C4AI Command R7B is a multilingual model trained on 23 languages.

### Model Details

**Model Architecture:** This is an auto-regressive language model that uses an optimized transformer architecture. After pretraining, this model uses supervised fine-tuning (SFT) and preference training to align model behavior to human preferences for helpfulness and safety. The model features three layers with sliding window attention (window size 4096) and ROPE for efficient local context modeling and relative positional encoding. A fourth layer uses global attention without positional embeddings, enabling unrestricted token interactions across the entire sequence.

**Languages covered:** The model has been trained on 23 languages: English, French, Spanish, Italian, German, Portuguese, Japanese, Korean, Arabic, Chinese, Russian, Polish, Turkish, Vietnamese, Dutch, Czech, Indonesian, Ukrainian, Romanian, Greek, Hindi, Hebrew, and Persian.

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