onnx-coreml VS Llama-2-Onnx

Compare onnx-coreml vs Llama-2-Onnx and see what are their differences.

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onnx-coreml Llama-2-Onnx
1 3
378 994
- 1.1%
10.0 6.7
almost 4 years ago 5 months ago
Python Python
MIT License GNU General Public License v3.0 or later
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onnx-coreml

Posts with mentions or reviews of onnx-coreml. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-08-10.

Llama-2-Onnx

Posts with mentions or reviews of Llama-2-Onnx. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-09-12.
  • Show HN: Fine-tune your own Llama 2 to replace GPT-3.5/4
    8 projects | news.ycombinator.com | 12 Sep 2023
    System: Here's some docs, answer concisely in a sentence.

    YMMV on cost still, depends on cloud vendor, and my intuition & viewpoint agrees with yours, GPT-3.5 is priced low enough that there isn't a case where it makes sense to use another model.

    It strikes me now that _very_ likely and not just our intuition: OpenAI's $/GPU hour is likely <= any other vendor's.

    The next big step will come from formalizing the stuff rolling around the local LLM community, for months now it's either been one-off $X.c stunts that run on desktop, and the vast majority of the _actual_ usage and progress is coming from porn-y stuff, like all nascent tech.

    Microsoft has LLaMa-2 ONNX available on GitHub[1]. There's budding but very small projects in different languages to wrap ONNX. Once there's a genuine cross-platform[2] ONNX wrapper that makes running LLaMa-2 easy, there will be a step change. It'll be "free"[3] to run your fine-tuned model that does as well as GPT-4 .

    It's not clear to me exactly when this will occur. It's "difficult" now, but only because the _actual usage_ in the local LLM community doesn't have a reason to invest in ONNX, and it's extremely intimidating to figure out how exactly to get LLaMa-2 running in ONNX. Microsoft kinda threw it up on GitHub and moved on, the sample code even still needs a PyTorch model. I see at least one very small company on HuggingFace that _may_ have figured out full ONNX.

    [1] https://github.com/microsoft/Llama-2-Onnx

  • FLaNK Stack Weekly for 14 Aug 2023
    32 projects | dev.to | 14 Aug 2023
  • Llama 2 on ONNX runs locally
    5 projects | news.ycombinator.com | 10 Aug 2023

What are some alternatives?

When comparing onnx-coreml and Llama-2-Onnx you can also consider the following projects:

llama.cpp - LLM inference in C/C++

vllm - A high-throughput and memory-efficient inference and serving engine for LLMs

SHARK - SHARK - High Performance Machine Learning Distribution

pkgx - the last thing you’ll install

OpenPipe - Turn expensive prompts into cheap fine-tuned models

awesome-data-temporality - A curated list to help you manage temporal data across many modalities 🚀.

gpt-llm-trainer

feldera - Feldera Continuous Analytics Platform

llama2.c - Inference Llama 2 in one file of pure C

fluent-bit - Fast and Lightweight Logs and Metrics processor for Linux, BSD, OSX and Windows

symmetric-ds - SymmetricDS is database replication and file synchronization software that is platform independent, web enabled, and database agnostic. It is designed to make bi-directional data replication fast, easy, and resilient. It scales to a large number of nodes and works in near real-time across WAN and LAN networks.

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InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
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