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microsoft
Llama-2-Onnx
Python2023–2023
microsoft / Llama-2-Onnx

Llama-2-Onnx

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2Distinct people
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0Explicit recommenders
1KGitHub stars
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This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by week2 dated mentions

Observed mentions: 2023-08-10 21:37:17 UTC to 2023-09-12 18:50:21 UTC. Weeks start Monday, UTC.

012023-08-07 00:00:00 UTC to 2023-08-14 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsAug 72023-08-14 00:00:00 UTC to 2023-08-21 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-08-21 00:00:00 UTC to 2023-08-28 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsAug 212023-08-28 00:00:00 UTC to 2023-09-04 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-09-04 00:00:00 UTC to 2023-09-11 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-09-11 00:00:00 UTC to 2023-09-18 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsSep 11

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

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PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Aug 72023-08-07 00:00:00 UTC2023-08-14 00:00:00 UTC110
Aug 142023-08-14 00:00:00 UTC2023-08-21 00:00:00 UTC000
Aug 212023-08-21 00:00:00 UTC2023-08-28 00:00:00 UTC000
Aug 282023-08-28 00:00:00 UTC2023-09-04 00:00:00 UTC000
Sep 42023-09-04 00:00:00 UTC2023-09-11 00:00:00 UTC000
Sep 112023-09-11 00:00:00 UTC2023-09-18 00:00:00 UTC101

What Hacker News says

2 sources
For use cases well within the capabilities of an LLM from last year, fine-tuned LLaMa 2 13B should/will blow ChatGPT out of the water: think "rate the sentiment of this text from 0-10". I believe this because LLaMa-2 13B is more than good enough to handle what I call "quick search", i.e. ``` User: "What's the weather in Milwaukee?" System: Here's some docs, answer concisely in one sentence. AI: It's 73 degrees Farenheit. ``` YMMV on cost still, depends on cloud vendor, and my intuition 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's there's a good reason for that intuition: OpenAI's $/GPU hour is likely <= any other vendor's and inference time of LLaMa 2 ~= GPT. I do think this will change with local LLMs. They've been way over-hyped for months, bu
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t after LLaMa 2, the challenges remaining are more sociological than technical. For months now it's been one-off $LATEST_BUZZY_MODEL.c stunts that run on desktop. The vast majority of the _actual_ usage and progress is coming from porn-y stuff, and the investment occurs in one-off stunts. That split of effort, and lack of engineering rigor, is stunting progress overall. 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. Funnily enough, ONNX is getting a spike in mindshare over the last month in the _Stable Diffusion_ community. There's decent cross-pollination between local art and local LLMs, ex. LoRA's were first a thing for Stable Diffusion. So I'm hoping we see this sooner rather than later. [1] https://github.com/microsoft/Llama-2-Onnx [2] Definition of cross-platform matters a ton here, what I mean is "I can import $ONNX_WRAPPER_LIB on iOS / Android / Mac / Windows and call Llama2.reply(String prompt, ...)" [3] Runs on somebody else's computer, where "somebody else" is the user, instead of a cloud vendor.
In Fine-tune your own Llama 2 to replace GPT-3.5/4

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