Codellama 34b



The model, codellama-34b, is a 34 billion parameter AI model that is designed to write and understand code and engage in conversations. Its primary function involves transforming textual prompts into coding language. The text-to-text model accepts inputs including debug mode, parameters for randomness control (top_k and top_p), the prompt as string, temperature for controlling the randomness of its output, and the maximum and/or minimum new tokens to generate. The output produced by the model seems to be structured in a token-wise form, primarily showcasing the generation of common features of a coding language such as function definitions, comments, variable assignments, and mathematical operations.

Use cases

Codellama-34b, as an AI model, can be integrated into a plethora of distinctive use cases given its powerful coding and conversational capabilities. The model can be used in the development of educational applications aimed at teaching programming to students, as it can interpret prompts and generate codes in response. Its text-to-text processing feature can also be harnessed by companies to facilitate the automatic translation of technical jargon into simple, layman terms, making it useful in customer service chatbots or interfaces. Furthermore, it could be utilized in programming tools where it could provide real-time code suggestions or corrections. In an innovation context, this model could be instrumental in creating a voice-to-code application where verbal coding instructions get converted into syntactically correct code. Additionally, because of its conversational abilities, the model could assist developers in brainstorming sessions by producing code snippets based on verbalized ideas.



Cost per run
Avg run time

Creator Models

Llama 2 13b$?17,926
Llama 2 13b Chat$?1,592,213
Codellama 13b$?71,820
Codellama 7b$?11,084

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Summary of this model and related resources.

Model NameCodellama 34b
A 34 billion parameter Llama tuned for coding and conversation
Model LinkView on Replicate
API SpecView on Replicate
Github LinkView on Github
Paper LinkView on Arxiv


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