💻 programming

c4ai-command-r7b-12-2024

7B parameter multilingual text generation model

#text generation
#multilingual
#Retrieval enhancement generation
#dialogue model
#Coding ability
c4ai-command-r7b-12-2024

Product Details

CohereForAI/c4ai-command-r7b-12-2024 is a 7B parameter multi-language model focused on high-level tasks such as reasoning, summarization, question answering and code generation. The model supports Retrieval Augmented Generation (RAG) and tool usage, enabling the use and combination of multiple tools to complete more complex tasks. It excels in enterprise-related code use cases and supports 23 languages.

Main Features

1
• Multi-language support: The model supports 23 languages, including English, French, Spanish, etc.
2
• Advanced reasoning capabilities: Optimized for complex tasks such as reasoning, summarizing, and question answering.
3
• Retrieval Augmented Generation (RAG): Specifically trained for RAG tasks, combining retrieval and generation.
4
• Tool usage capabilities: Ability to interact with external tools such as APIs, databases or search engines.
5
• Coding skills: Excellent performance in enterprise-related coding scenarios, including SQL and code translation.
6
• Dialogue and command mode: Can be configured as dialogue model and command model to optimize the interactive experience.
7
• Security and Compliance: Follows the CC-BY-NC license and C4AI’s Acceptable Use Policy.

How to Use

1
1. Install necessary libraries, such as transformers, from the source code repository.
2
2. Import AutoTokenizer and AutoModelForCausalLM.
3
3. Initialize the tokenizer and model using the model ID.
4
4. Prepare to enter the message and apply the chat template using tokenizer.
5
5. Use model.generate to generate text.
6
6. Use tokenizer.decode to decode the generated text.
7
7. Print or use the generated text.

Target Users

The target audience is researchers, developers, and enterprise users who require a high-performance model capable of handling multilingual and complex tasks, especially in the areas of code generation and natural language processing.

Examples

Use models to generate code snippets for a specific programming language.

Apply models in chatbots to provide multi-language support and conversational capabilities.

Used in enterprises for data analysis to generate SQL queries and data summaries through models.

Quick Access

Visit Website →

Categories

💻 programming
› code assistant
› Model training and deployment

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