phasellm
llama.cpp
phasellm | llama.cpp | |
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14 | 777 | |
443 | 57,984 | |
- | - | |
8.9 | 10.0 | |
3 months ago | 2 days ago | |
Python | C++ | |
MIT License | MIT License |
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phasellm
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Ask HN: Any recommended AI tools to analyze data and generate insights?
If you're looking for an open source solution you can customize, check out the ResearchLLM demo: https://phasellm.com/researchllm
Code: https://github.com/wgryc/phasellm/tree/main/demos-and-produc...
- PhaseLLM Eval: run batch LLM jobs and evals via visual front-end (MIT licensed)
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To everyone who is using alternative bots (e.g. Claude) - your comparisons?
Using Claude, Cohere, GPT-4, OpenAssistant. Formally swapping between them using PhaseLLM (open source library similar to LangChain).
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April 2023
Large language model evaluation and workflow framework from Phase AI. (https://github.com/wgryc/phasellm)
- Ask HN: Freelancer? Seeking freelancer? (June 2023)
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ResearchGPT: Automated Data Analysis and Interpretation
Fantastic questions! Re: working/not working at times -- this is still an issue. It's why I'm building PhaseLLM more broadly (https://github.com/wgryc/phasellm) -- need a robust pipeline that can also "reset" parts of itself if an LLM makes errors or mistakes.
You can see my prompts in this file: https://github.com/wgryc/phasellm/blob/main/demos-and-produc... I autogenerate a fairly big starting prompt and keep resubmitting it. It describes the data set extensively, which helps quite a bit.
That being said, a lot more can be done here around prompt optimization + making this more robust.
- ResearchGPT: LLMs to write stats code, analyze, and interpret results for you
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Best way to use GPT offline with own content?
That being said, you might want to actually run head-to-head tests between models. PhaseLLM (free, open source) allows you to build a workflow and plug and play various models (including Dolly 2.0 and GPT-4). Then you can run tests to see how much worse/better the various LLMs are and if that's acceptable for your use case.
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12-Apr-2023 AI Summary
Large language model evaluation and workflow framework from Phase AI. (https://github.com/wgryc/phasellm)
- PhaseLLM: Standardized Chat LLM API (Cohere, Claude, GPT) + Evaluation Framework
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?
awesome-chatgpt - 🧠 A curated list of awesome ChatGPT resources, including libraries, SDKs, APIs, and more. 🌟 Please consider supporting this project by giving it a star.
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.
telegram-chatgpt-concierge-bot - Interact with OpenAI's ChatGPT via Telegram and Voice.
gpt4all - gpt4all: run open-source LLMs anywhere
DeepSpeed - DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
rel-events - The relevant React Events Library.
GPTQ-for-LLaMa - 4 bits quantization of LLaMA using GPTQ
kivy - Open source UI framework written in Python, running on Windows, Linux, macOS, Android and iOS
ggml - Tensor library for machine learning
prompt-engineering - ChatGPT Prompt Engineering for Developers - deeplearning.ai
alpaca.cpp - Locally run an Instruction-Tuned Chat-Style LLM