openplayground
llama.cpp
openplayground | llama.cpp | |
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12 | 782 | |
6,108 | 58,425 | |
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0.6 | 10.0 | |
15 days ago | 4 days ago | |
TypeScript | C++ | |
MIT License | MIT License |
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openplayground
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Show HN: Unified access to top AI models, supporting GPT4, Claude and more
https://github.com/nat/openplayground
I load up $5 into my account using my credit card and then reload it whenever it gets low, it also has a tab for comparing multiple resulta from different models together.
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I love how many people want a way bigger context window for example for GPT-4 (like 100k-1m). May I introduce you the cost of one API call at the full 32k context window? 2$. So 1m would approximately cost you 60$. One call. 60$.
https://github.com/nat/openplayground https://discord.gg/uT98U9HJ.
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How good is the 100k context model?
Try here: https://github.com/nat/openplayground
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Performance of GPT-4 vs PaLM 2
From there you have lots of other models: One of the best places to easily start using multiple models is using a multiple model UI program lik GPT4All, there are also some programs that provide access to more models or use different ways of interfacing with them, here are some of what I've found are the best / most popular programs to play around with lots of different models and compare them: LocalAI, text-generation-webui, open playground
- Show HN: Promptfoo – a tool for comparing LLM prompts and models
- Show HN: AI Playground by Vercel Labs
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What is this subreddit about? I can't tell if its wifaus or locally run LLMs
Here's another interesting engine called AI playground that lets you do side-by-side comparisons of language models based on the same prompts: https://github.com/nat/openplayground
- An LLM playground you can run on your laptop
llama.cpp
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IBM Granite: A Family of Open Foundation Models for Code Intelligence
if you can compile stuff, then looking at llama.cpp (what ollama uses) is also interesting: https://github.com/ggerganov/llama.cpp
the server is here: https://github.com/ggerganov/llama.cpp/tree/master/examples/...
And you can search for any GGUF on huggingface
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Ask HN: Affordable hardware for running local large language models?
Yes, Metal seems to allow a maximum of 1/2 of the RAM for one process, and 3/4 of the RAM allocated to the GPU overall. There’s a kernel hack to fix it, but that comes with the usual system integrity caveats. https://github.com/ggerganov/llama.cpp/discussions/2182
- Xmake: A modern C/C++ build tool
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Better and Faster Large Language Models via Multi-Token Prediction
For anyone interested in exploring this, llama.cpp has an example implementation here:
https://github.com/ggerganov/llama.cpp/tree/master/examples/...
- Llama.cpp Bfloat16 Support
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Fine-tune your first large language model (LLM) with LoRA, llama.cpp, and KitOps in 5 easy steps
Getting started with LLMs can be intimidating. In this tutorial we will show you how to fine-tune a large language model using LoRA, facilitated by tools like llama.cpp and KitOps.
- GGML Flash Attention support merged into llama.cpp
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Phi-3 Weights Released
well https://github.com/ggerganov/llama.cpp/issues/6849
- Lossless Acceleration of LLM via Adaptive N-Gram Parallel Decoding
- Llama.cpp Working on Support for Llama3
What are some alternatives?
BetterChatGPT - An amazing UI for OpenAI's ChatGPT (Website + Windows + MacOS + Linux)
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
gpt4all - gpt4all: run open-source LLMs anywhere
promptfoo - Test your prompts, models, and RAGs. Catch regressions and improve prompt quality. LLM evals for OpenAI, Azure, Anthropic, Gemini, Mistral, Llama, Bedrock, Ollama, and other local & private models with CI/CD integration.
ChatALL - Concurrently chat with ChatGPT, Bing Chat, Bard, Alpaca, Vicuna, Claude, ChatGLM, MOSS, 讯飞星火, 文心一言 and more, discover the best answers
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
galai - Model API for GALACTICA
ggml - Tensor library for machine learning
awesome-ml - Curated list of useful LLM / Analytics / Datascience resources
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM