meta-llama/llama-recipes
Scripts for fine-tuning Llama2 with composable FSDP & PEFT methods to cover single/multi-node GPUs. Supports default & custom datasets for applications such as summarization & question answering. Supporting a number of candid inference solutions such as HF TGI, VLLM for local or cloud deployment.Demo apps to showcase Llama2 for WhatsApp & Messenger
Language:Jupyter Notebook
Total stars: 8361
Stars trend:
#jupyternotebook
#ai, #finetuning, #langchain, #llama, #llama2, #llm, #machinelearning, #python, #pytorch, #vllm
Scripts for fine-tuning Llama2 with composable FSDP & PEFT methods to cover single/multi-node GPUs. Supports default & custom datasets for applications such as summarization & question answering. Supporting a number of candid inference solutions such as HF TGI, VLLM for local or cloud deployment.Demo apps to showcase Llama2 for WhatsApp & Messenger
Language:Jupyter Notebook
Total stars: 8361
Stars trend:
18 Apr 2024
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19 Apr 2024
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#ai, #finetuning, #langchain, #llama, #llama2, #llm, #machinelearning, #python, #pytorch, #vllm
mustafaaljadery/llama3v
A SOTA vision model built on top of llama3 8B.
Language:Python
Total stars: 125
Stars trend:
#python
#llama, #llama3, #vllm
A SOTA vision model built on top of llama3 8B.
Language:Python
Total stars: 125
Stars trend:
28 May 2024
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3am █▉ +15#python
#llama, #llama3, #vllm
containers/ramalama
The goal of RamaLama is to make working with AI boring.
Language:Shell
Total stars: 640
Stars trend:
#shell
#ai, #containers, #inferenceserver, #llamacpp, #llm, #podman, #vllm
The goal of RamaLama is to make working with AI boring.
Language:Shell
Total stars: 640
Stars trend:
31 Jan 2025
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4pm ████▉ +39#shell
#ai, #containers, #inferenceserver, #llamacpp, #llm, #podman, #vllm
meta-llama/llama-cookbook
Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services
Language:Jupyter Notebook
Total stars: 16761
Stars trend:
#jupyternotebook
#ai, #finetuning, #langchain, #llama, #llama2, #llm, #machinelearning, #python, #pytorch, #vllm
Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services
Language:Jupyter Notebook
Total stars: 16761
Stars trend:
7 Apr 2025
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#ai, #finetuning, #langchain, #llama, #llama2, #llm, #machinelearning, #python, #pytorch, #vllm
OpenBMB/UltraRAG
UltraRAG v2: Less Code, Lower Barrier, Faster Deployment! MCP-based low-code RAG framework, enabling researchers to build complex pipelines to creative innovation.
Language:Python
Total stars: 2018
Stars trend:
#python
#bgem3, #deepseek, #easy, #embedding, #gpt, #jina, #llm, #mcp, #mcpclient, #mcpserver, #openai, #qwen, #rag, #sentencetransformers, #vllm
UltraRAG v2: Less Code, Lower Barrier, Faster Deployment! MCP-based low-code RAG framework, enabling researchers to build complex pipelines to creative innovation.
Language:Python
Total stars: 2018
Stars trend:
19 Nov 2025
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#bgem3, #deepseek, #easy, #embedding, #gpt, #jina, #llm, #mcp, #mcpclient, #mcpserver, #openai, #qwen, #rag, #sentencetransformers, #vllm