Model Hosting Improvements Metabug Issue 184 Smallcloudai Refact

Model Hosting Improvements Metabug Issue 184 Smallcloudai Refact => the result is the user can understand the situation, delete the model that doesn't work, add again with a smaller context. Self hosted version of refact is a more flexible option with additional features. it allows you to create fine tuned models for your specific task. self hosted version is designed for developers who want to have a full control over their refact experience. the easiest way to run this server is a pre build docker image.

Supported Models In Refact Ai Refact Documentation We encountered an error trying to load issues. Fine tuning is a process of pretraining a base model to improve the quality of generated code. fine tuning is supported in the following version of refact.ai: fine tuning can be particularly useful for: adapting the model to a specific programming language. customizing the model for a particular technology stack. Refact.ai agent accesses your resources and handles related operations autonomously, mimicking your workflow. ⚡ free, unlimited, context aware auto completion: code faster with smart ai suggestions. 🛠️ supports 25 programming languages: python, javascript, java, rust, typescript, php, c , c#, go, and many more!. I saw refact.ai self hosted version can support 3rd party apis by adding url and key. could you do the similar to support any ollama managed local model for code completion chat finetuning?.

Supported Models In Refact Ai Refact Documentation Refact.ai agent accesses your resources and handles related operations autonomously, mimicking your workflow. ⚡ free, unlimited, context aware auto completion: code faster with smart ai suggestions. 🛠️ supports 25 programming languages: python, javascript, java, rust, typescript, php, c , c#, go, and many more!. I saw refact.ai self hosted version can support 3rd party apis by adding url and key. could you do the similar to support any ollama managed local model for code completion chat finetuning?. New models: llama3.1, llama3.2 and qwen2.5 coder families. new providers support: 3rd party apis for groq and cerebras. support for multiline code completion models. new models: last openai models is now available in docker. tool usage support for 3rd party models: turn on 3rd party apis to use latest features of refact. removed deprecated models. We've updated refact self hosted version following feedback and suggestions, so that it's now completely self contained without the need to login and collect telemetry. the model is no longer fetching from outside, it will pass with env variable. it offers a choice of 2 of our own refact models: 3b and 0.3b. A benchmarking tool for evaluating ai coding assistants on real world software engineering tasks from the swe bench dataset. For the base model, we used our own dataset that contains code with permissive licenses only, and open text datasets. filtering is the key to success of this model: the text to code proportion was 50:50, model trained for 1.2t tokens.

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The Replicated Platform Overview

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