llama3
ollama
| llama3 | ollama | |
|---|---|---|
| 17 | 212 | |
| 20,272 | 66,540 | |
| 15.0% | 23.9% | |
| 8.9 | 9.9 | |
| 4 days ago | 3 days ago | |
| Python | Go | |
| GNU General Public License v3.0 or later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
llama3
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Hindi-Language AI Chatbot for Enterprises Using Qdrant, MLFlow, and LangChain
Now, let's start building the next part of the chatbot. In this part, we will be using the LLM from Ollama and integrating it with the chatbot. More particularly, we will be using the Llama-3 model. Llama-3 is Meta's latest and most advanced open-source large language model (LLM). It is the successor to the previous Llama 2 model and represents a significant improvement in performance across a variety of benchmarks and tasks. Llama 3 comes in two main versions - an 8 billion parameter model and a 70 billion parameter model. Llama 3 supports longer context lengths of up to 8,000 tokens.
- FLaNK AI-April 22, 2024
- Meta Llama 3 GitHub
- Mark Zuckerberg himself appears in the list of direct contributors to Llama 3
- Mark Zuckerberg: Llama 3, $10B Models, Caesar Augustus, Bioweapons [video]
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Llama 3 in [8B and 70B] sizes is out
What is fascinating is how the smaller 8B version outperformed the bigger previus-gen 70B model in every benchmark listed on the model card:
- Llama 3 GitHub Repository
- Meta Llama 3
ollama
- Ollama v0.1.34 Is Out
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Ask HN: What do you use local LLMs for?
- Basic internet search (I start ollama CLI faster than I can start a browser - https://ollama.com)
- Formatting/changing text
- Troubleshooting code, esp. new frameworks/libs
- Recipes
- Data entry
- Organizing thoughts: High-level lists, comparison, classification, synonyms, jargon & nomenclature
- Learning esp. by analogy and example
RAG for:
- Website assistants (https://github.com/bennyschmidt/ragdoll-studio/tree/master/e...)
- Game NPCs (https://github.com/bennyschmidt/ragdoll-studio/tree/master/e...)
- Discord/Slack/forum bots (https://github.com/bennyschmidt/ragdoll-studio/tree/master/e...)
- Character-driven storytelling and creating art in a specific style for video game loading screens, background images, avatars, website art, etc. (https://github.com/bennyschmidt/ragdoll-studio/tree/master/r...)
- FLaNK-AIM Weekly 06 May 2024
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Introducing Jan
Jan goes a step further by integrating with other local engines like LM Studio and ollama.
- Ollama v0.1.33
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Hindi-Language AI Chatbot for Enterprises Using Qdrant, MLFlow, and LangChain
# install the Ollama curl -fsSL https://ollama.com/install.sh | sh # get the llama3 model ollama pull llama2 # install the MLFlow pip install mlflow
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Create an AI prototyping environment using Jupyter Lab IDE with Typescript, LangChain.js and Ollama for rapid AI prototyping
Ollama for running LLMs locally
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Setup Llama 3 using Ollama and Open-WebUI
curl -fsSL https://ollama.com/install.sh | sh
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Ollama v0.1.33 with Llama 3, Phi 3, and Qwen 110B
Streaming is not a problem (it's just a simple flag: https://github.com/wiktor-k/llama-chat/blob/main/index.ts#L2...) but I've never used voice input.
The examples show image input though: https://github.com/ollama/ollama/blob/main/docs/api.md#reque...
Maybe you can file an issue here: https://github.com/ollama/ollama/issues
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I Said Goodbye to ChatGPT and Hello to Llama 3 on Open WebUI - You Should Too
I’m a huge fan of open source models, especially the newly release Llama 3. Because of the performance of both the large 70B Llama 3 model as well as the smaller and self-host-able 8B Llama 3, I’ve actually cancelled my ChatGPT subscription in favor of Open WebUI, a self-hostable ChatGPT-like UI that allows you to use Ollama and other AI providers while keeping your chat history, prompts, and other data locally on any computer you control.
What are some alternatives?
promptfoo - Test your prompts. Evaluate and compare LLM outputs, catch regressions, and improve prompt quality. [Moved to: https://github.com/promptfoo/promptfoo]
llama.cpp - LLM inference in C/C++
gpt4all - gpt4all: run open-source LLMs anywhere
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
private-gpt - Interact with your documents using the power of GPT, 100% privately, no data leaks
llama - Inference code for Llama models
LocalAI - :robot: The free, Open Source OpenAI alternative. Self-hosted, community-driven and local-first. Drop-in replacement for OpenAI running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. It allows to generate Text, Audio, Video, Images. Also with voice cloning capabilities.
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI
exllama - A more memory-efficient rewrite of the HF transformers implementation of Llama for use with quantized weights.
text-generation-inference - Large Language Model Text Generation Inference
litellm - Call all LLM APIs using the OpenAI format. Use Bedrock, Azure, OpenAI, Cohere, Anthropic, Ollama, Sagemaker, HuggingFace, Replicate (100+ LLMs)
llama-cpp-python - Python bindings for llama.cpp