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Codestral Mamba
Codestral Mamba
C
Codestral Mamba
AI code generationAI development assistant#Code Generation#Linear Inference#Infinite Sequences#Apache 2.0English PicksPaid
Overview :
Codestral Mamba is an advanced code generation language model developed by Mistral AI team based on Mamba2 architecture. It features the benefits of linear time inference and the ability to theoretically model infinitely long sequences. The model has been professionally trained and possesses advanced code and inference capabilities that can compete with the current state-of-the-art Transformer-based models.
Target Users :
Codestral Mamba is primarily aimed at developers and teams who need to enhance code productivity. It achieves this through rapid code generation and inference capabilities, helping users save time during programming tasks and improve work efficiency, particularly suitable for scenarios involving a large amount of code and complex logic.
Total Visits： 11.7M
Top Region： FR(36.13%)
Website Views ： 53.5K
Use Cases
Assisting developers as a local code generator.
Providing new insights for architectural research, driving technological advancements.
Used in conjunction with Codestral 22B to provide different model size choices.
Features
Linear time inference for fast responses to long inputs.
Theoretically capable of processing infinitely long sequences.
Advanced code and inference capabilities, comparable to cutting-edge Transformer models.
Support for context retrieval with up to 256k tokens.
Can be deployed using the mistral-inference SDK.
Supports local inference with TensorRT-LLM and llama.cpp.
Free to use, modify, and distribute under the terms of the Apache 2.0 license.
How to Use
1. Download the mistral-inference SDK.
2. Obtain the original weights of Codestral Mamba from HuggingFace.
3. Deploy the Codestral Mamba model using the SDK.
4. Configure TensorRT-LLM or llama.cpp for local inference according to your needs.
5. Test the model on la Plateforme (codestral-mamba-2407).
6. Leverage the model's advanced code and inference capabilities to solve real-world programming problems.
7. Use, modify, and distribute the model freely in accordance with the terms of the Apache 2.0 license.
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