gpt-json
llama.cpp
gpt-json | llama.cpp | |
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7 | 779 | |
726 | 57,984 | |
- | - | |
6.8 | 10.0 | |
about 1 month ago | 4 days ago | |
Python | C++ | |
MIT License | MIT License |
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gpt-json
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Structured Output from LLMs (Without Reprompting!)
I did a POC project with it recently. The guidance on gpt-3.5-turbo and gpt-4 models isn't as functional as plain gpt-3. I found I had better results using https://github.com/piercefreeman/gpt-json and it doesn't require multiple calls to the API. Not as feature filled, but it may meet your needs
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This week's top indie A.I projects, launches and resources
Gpt-json: Structured and typehinted GPT responses in Python
- GitHub - piercefreeman/gpt-json: Structured and typehinted GPT responses in Python
- Show HN: GPT-JSON – Structured and typehinted GPT responses in Python
- GPT-JSON: Structured and typehinted GPT responses in Python
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?
zod-chatgpt
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
jsonformer - A Bulletproof Way to Generate Structured JSON from Language Models
gpt4all - gpt4all: run open-source LLMs anywhere
emdash - 📚🧙♂️ Wisdom indexer — use AI to organize text snippets so you can actually remember & learn from what you read
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
evadb - Database system for AI-powered apps
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
struct-gpt - get structured output from LLM's
ggml - Tensor library for machine learning
open_llama - OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s LLaMA 7B trained on the RedPajama dataset
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM