{"id":26758229,"url":"https://github.com/ksm26/getting-started-with-mistral","last_synced_at":"2025-07-14T15:37:51.666Z","repository":{"id":238723214,"uuid":"797366605","full_name":"ksm26/Getting-Started-with-Mistral","owner":"ksm26","description":"Explore Mistral AI's extensive collection of models. Learn to select, prompt, and integrate Mistral's open-source and commercial models for tasks like classification, coding, and Retrieval Augmented Generation (RAG).","archived":false,"fork":false,"pushed_at":"2024-05-17T10:25:10.000Z","size":59,"stargazers_count":3,"open_issues_count":0,"forks_count":2,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-03-28T16:18:54.927Z","etag":null,"topics":["advanced-coding","ai-models","api-integration","commercial-models","effective-prompting","embeddings","function-calling","llm-capabilities","machine-learning","mistral-ai","mixtral-models","model-selection","open-source-models","python-integration","rag","similarity-search","structured-responses","web-interface"],"latest_commit_sha":null,"homepage":"https://www.deeplearning.ai/short-courses/getting-started-with-mistral/","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ksm26.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-05-07T17:33:39.000Z","updated_at":"2025-02-25T03:44:24.000Z","dependencies_parsed_at":"2024-05-16T08:30:15.643Z","dependency_job_id":null,"html_url":"https://github.com/ksm26/Getting-Started-with-Mistral","commit_stats":null,"previous_names":["ksm26/getting-started-with-mistral"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ksm26/Getting-Started-with-Mistral","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksm26%2FGetting-Started-with-Mistral","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksm26%2FGetting-Started-with-Mistral/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksm26%2FGetting-Started-with-Mistral/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksm26%2FGetting-Started-with-Mistral/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ksm26","download_url":"https://codeload.github.com/ksm26/Getting-Started-with-Mistral/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ksm26%2FGetting-Started-with-Mistral/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":265313287,"owners_count":23745188,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["advanced-coding","ai-models","api-integration","commercial-models","effective-prompting","embeddings","function-calling","llm-capabilities","machine-learning","mistral-ai","mixtral-models","model-selection","open-source-models","python-integration","rag","similarity-search","structured-responses","web-interface"],"created_at":"2025-03-28T16:18:57.404Z","updated_at":"2025-07-14T15:37:51.636Z","avatar_url":"https://github.com/ksm26.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🌐 [Getting Started with Mistral](https://www.deeplearning.ai/short-courses/getting-started-with-mistral/)\n\n🔍 Dive into the world of Mistral AI with the \"Getting Started with Mistral\" course! This course will walk you through accessing and utilizing Mistral's collection of open-source and commercial models for various tasks.\n\n## Course Summary\nIn this course, you'll explore Mistral AI's diverse collection of open-source and commercial models, including the Mixtral 8x7B and Mixtral 8x22B models. Here's what you'll learn:\n\n1. 🧩 **Model Selection**: Understand how to select the right Mistral model based on task complexity and speed requirements.\n2. 🛠️ **Effective Prompting Techniques**: Learn to prompt Mistral models effectively for tasks ranging from simple classification to advanced coding.\n3. 📊 **Function Calling**: Utilize Mistral's native function calling to integrate traditional code functionalities with LLM capabilities.\n4. 🔄 **Retrieval Augmented Generation (RAG)**: Build a basic RAG system from scratch, incorporating similarity search and embeddings.\n\n## Key Points\n- 🚀 Access Mistral's diverse range of open-source and commercial models, including the Mixtral 8x22B, via web interface and API calls.\n- 💻 Leverage Mistral's JSON mode to generate structured LLM responses, facilitating integration into larger software applications.\n- 🔄 Enhance LLM capabilities by calling user-defined Python functions through Mistral's API, enabling tasks like web searches and database retrieval.\n\n## About the Instructor\n🌟 **Sophia Yang** is the Head of Developer Relations at Mistral AI, bringing her expertise to guide you through leveraging Mistral's cutting-edge models effectively.\n\n🔗 Enroll in the course or learn more at [deeplearning.ai](https://www.deeplearning.ai/short-courses/).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fksm26%2Fgetting-started-with-mistral","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fksm26%2Fgetting-started-with-mistral","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fksm26%2Fgetting-started-with-mistral/lists"}