awesome-chatgpt-api
llama.cpp
| awesome-chatgpt-api | llama.cpp | |
|---|---|---|
| 4 | 776 | |
| 5,665 | 57,463 | |
| - | - | |
| 4.3 | 10.0 | |
| about 1 month ago | 6 days ago | |
| Python | C++ | |
| - | MIT License |
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awesome-chatgpt-api
- Curated list of apps and tools that allow ChatGPT API keys
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LLM, ttok and strip-tags–CLI tools for working with ChatGPT and other LLMs
There's an awesome list for BYOK (bring your own key) projects here: https://github.com/reorx/awesome-chatgpt-api#cli
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GPT-4 just changed its message limit to 50 every 4 hours instead of 100
My plan is to go through the tools here, https://github.com/reorx/awesome-chatgpt-api, and hopefully some other sites, find one that's ChatGPT-like but local, and then use the API. My math puts me at around $3-5/month on GPT-3.5 and $30-40 on GPT-4 if I used it a lot via the API. I expect to be more choosey about when I use GPT-4, though.
- Curated list of ChatGPT apps using configurable API keys
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?
whatsapp-web.js - A WhatsApp client library for NodeJS that connects through the WhatsApp Web browser app
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
bashGPT - Use ChatGPT, GPT-3 and other models from the command line.
gpt4all - gpt4all: run open-source LLMs anywhere
mods - AI on the command line
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
askai - Command Line Interface for OpenAi ChatGPT
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
cass - A ChatGPT-powered assistant in the console
ggml - Tensor library for machine learning
shell_gpt - A command-line productivity tool powered by AI large language models like GPT-4, will help you accomplish your tasks faster and more efficiently.
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM