Microsoft Phi-4 GGUF available. Download link in the post

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rbgo404@reddit

Here’s a GGUF version with vLLM: https://github.com/inferless/phi4-vllm-gguf

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robiinn@reddit

Uploaded them to ollama in case anyone want to use it from there. https://ollama.com/vanilj/Phi-4

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Inevitable-Fun-8757@reddit

Thank you 🙏 legend 🙌I don’t see tool use enabled in ollama ? Do you know how to enable it ?

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robiinn@reddit

I don't know tbh, sorry. You would probably need to edit the modelfile and the chat format to include that somehow.

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LeLeumon@reddit

Thank you! Do you think it might be possible for you to also upload fp16?

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robiinn@reddit

Sure, i'll upload it when I have downloaded it

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Awesome! Thank you very much! I actually found the fp16 version to be much better then q8, especially in translation tasks. q8 gives me the complete wrong result in a chain of translations that I tested.

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TeamDman@reddit

Thank you so very much! This seems a very capable model. I was able to use it to transform a justfile into a main.tf with a local_file resource block to convert each justfile action into an independent shell script

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Few_Painter_5588@reddit

Yoooo, you're the dude that uploaded Midnight-Miqu there. Thanks for that bro!

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robiinn@reddit

Np! I don't use it myself, but I saw that it was missing and a lot of people talked about it, so I though why not upload it. That is kinda how it is with all models I upload, trying to help people get easy access to models that are not uploaded by Ollama themself.

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RedKnightRG@reddit

The hero we need!

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isr_431@reddit

Perfect. Is it using chatml?

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robiinn@reddit

Kinda, you can find the exact template [here](https://huggingface.co/matteogeniaccio/phi-4/blob/9834d93de607af2c4542570b9e9e6613126ade3c/phi-4/tokenizer_config.json#L774), they seems to be seperating the messages with <|im_sep|>.

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AaronFeng47@reddit

Damn, this time it's legit! It can simply translate text without provide cringe explanations And summarise & translate a large amount of transcripts, perfectly followed system prompt This is waaaaay better than previous phi models!

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charmander_cha@reddit

eu acabei de traduzir 2 livros com ele, incrivel

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fairydreaming@reddit

It really is. In my farel-bench benchmark it performs on par with GPT-4o. Phi-3 medium had score 62.44, Phi-4 has 81.11.

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DeSibyl@reddit

Is Phi-4 good for coding? In comparison to say the new QWQ or Qwen2.5 72B (4.25bpw)

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rickyhatespeas@reddit

It was able to do something for me that gpt4o kept failing at, it wasn't that technical just a weird syntax thing it couldn't nail

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AaronFeng47@reddit

I just started testing this model so I can't tell if it's actually better than qwen2.5 14b But It's multilingual, it can follow instructions, it's much better than phi3, this time Microsoft really did it, now we have another series of "actually good & useful" open weight models!

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hummingbird1346@reddit

Please don't leave us hanging. I wanna know the comparison between qwen and this. Also thanks.

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Few_Painter_5588@reddit

I can corroborate AaronFeng47's comment. It's legit. I would say it's roughly equal if not a tad bit better than qwen 2.5 14b. However, don't go into this expecting this model to excel in creative writing, this model is very censored and very pedantic, which I suspect is why this model has such a low IFEVAL score. Also, Cohere did launch a new 7B model that beats out qwen 2.5 7b. So Qwen 2.5 no longer holds the crown in two areas. Finally, some competition!

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_yustaguy_@reddit

The Cohere model isn't even close to Qwen in terms of benchmarks.

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Few_Painter_5588@reddit

Qwen 2.5 7b? If so, it is according to the LLM leaderboard from huggingface

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FrostyContribution35@reddit

How is it compared to supernova medius?

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Short-Sandwich-905@reddit

What quant?

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swagonflyyyy@reddit

How censored is it?

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BlueSwordM@reddit

Quite a bit still. It's clear that the post-training was very sanitized and as always, it's clear that it is making the model a bit dumber.

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kraih@reddit

Looks like the license changed to [Microsoft Research License Agreement](https://techcommunity.microsoft.com/blog/aiplatformblog/introducing-phi-4-microsoft%E2%80%99s-newest-small-language-model-specializing-in-comple/4357090). That means non-commercial use only from now on.

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thatsusernameistaken@reddit

Which is reasonable. No? If that is a trade off for us getting these models then so be it. Better than mistral license model I hope. Does it mean that I could use it in my company for my employees, but not expose it to the public while charging them? These apis are fairly cheap now so it shouldn’t be a deal breaker.

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kraih@reddit

No, you cannot use it for commercial purposes. Doing so in secret does not make it any more legal.

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CryptoSpecialAgent@reddit

But doing so in secret makes it impossible to get caught - unlike, say, using pirated windows at your organization, there's absolutely no way anyone can prove what LLM you're using to power some end user product or internal tool unless you share the weights. LLMs by and large have no idea of their own identity and usually say they're either gpt-4 or Claude because most smaller models have been fine tuned on synthetic data generated by SOTA commercial models

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thatsusernameistaken@reddit

What does commercial in this settings mean? I understand selling it it like as a chat bot or similar. But is commercial also if it’s used in house and not exposed to any customers? What if it’s a non-profit company. Or government company?

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kraih@reddit

Any commercial use, speak with your lawyer or get sued at some point in the future.

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thatsusernameistaken@reddit

What constitutes as commercial usage?

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Amgadoz@reddit

That's up to the court to determine if Microsoft decides to sue you.

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imDaGoatnocap@reddit

Microsoft isn't going to sue anyone for secretly using Phi-4 internally for commercial use unless "anyone" is a large corporation. I'd love to see them try to sue me.

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Competitive_Travel16@reddit

There are ways around what you want. Talk to a lawyer.

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NewGeneral7964@reddit

No.

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paranoidray@reddit

Is this a good way to run it using llama.cpp ? llama-bin-win-cuda-cu12\llama-server.exe --n-gpu-layers 9999 --flash-attn --ctx-size 32768 -ctk q8_0 -ctv q8_0 --model gguf/phi-4-Q8_0.gguf

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paranoidray@reddit

-c 65536 -np 4 ?

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paranoidray@reddit

-np, --parallel N number of parallel sequences to decode (default: 1) (env: LLAMA_ARG_N_PARALLEL)

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bafil596@reddit

Got it running on Google Colab, works great! [Colab link](https://colab.research.google.com/github/Troyanovsky/Local-LLM-Comparison-Colab-UI/blob/main/phi_4.ipynb)

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Many_SuchCases@reddit

Thank you! I ran the only test that matters /s https://preview.redd.it/5xe5oj7s1n6e1.png?width=518&format=png&auto=webp&s=33fafd8ea486c7a41df29458b6793da65e7c33e0

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l7ucky@reddit

https://preview.redd.it/vr6ip5j9bh7e1.png?width=2076&format=png&auto=webp&s=397860f2512e392728e7a499a060763a4db3c61b Comparing this response to llama 3.2 is like trying to teach overconfident 2 year olds to count. 🤦

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matteogeniaccio@reddit (OP)

Well, it does answer correctly if you give it a little push: https://preview.redd.it/ol5y2tic2n6e1.png?width=894&format=png&auto=webp&s=1f2b765003cea474b2449189d8d0109eb771c7fe

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Uncle___Marty@reddit

Im pretty blown away. I sat with the model and did the following. 1.Asked the question and let it get it wrong. 2. told it the correct answer and asked it to understand why it got it wrong. 3. asked it to consider a way to prevent it from happening in the future. 4.Asked it to use that to make a system prompt so it till never happen again. Its output for the system prompt was : \------ Count Each Instance: When identifying occurrences of specific letters within words or phrases, ensure each letter is counted individually. Consider Consecutive Letters Separately: Treat consecutive instances (e.g., "rr") as separate entities and count them accordingly to avoid undercounting. Verification Step: After counting, perform a quick verification to confirm that no instances were overlooked, especially in sequences of the same letter. Review Before Finalizing: Take a moment to review your results, ensuring all logic steps have been applied correctly before providing the final count. \-------- I cant make it miscount the wrong amount no matter which word I give it. I'm mighty impressed it kind of taught itself a reasoning process with a little help from me.

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namankhator@reddit

Thanks for this.!!

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ab2377@reddit

this is really good!

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Maleficent-Ad5999@reddit

So run phi-4 in a loop and we have o1.??

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RenoHadreas@reddit

Wrap it up boys, this one ain't AGI either. Booooo.

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LoafyLemon@reddit

I'm waiting for a model that simply tells the person to 'fuck off' with such dumb questions like a true human would.

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RenoHadreas@reddit

Two years ago gpt 3.5 told me "No, make the table yourself. It's not very difficult" and that's the closest I have felt to AGI

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Homeschooled316@reddit

One time I asked gpt 4o about some microsoft documentation for an annoying cloud service issue I was having. It provided that same documentation as a reference for something I should read. I replied "gee, thanks for that documentation, I never would have found it otherwise." It replied, "Sarcasm noted," and went on to imply that I'm a bad software engineer for not being able to figure it out from the doc.

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thatsusernameistaken@reddit

🤣

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ab2377@reddit

😆 ty

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Factemius@reddit

What's the frontend for this ?

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matteogeniaccio@reddit (OP)

It's my own framework: [GraphLLM](https://github.com/matteoserva/GraphLLM)

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Factemius@reddit

Very cool, this should be useful to test and tinker LLMs and compare results

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RevolutionOn@reddit

Wow, really looks like comfyui but this is awesome, good job!

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RevolutionOn@reddit

Comfyui

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graphicaldot@reddit

u/AICodeKing Evaluated it on a set of 13 questions, and it is the only model that answered 12 questions correctly. Some of the questions include: * Write a Game of Life in Python that works in the terminal. * Generate the SVG code for a butterfly. * There are five people in a house (A, B, C, D, and E). A is watching TV with B, D is sleeping, B is eating a sandwich, and E is playing table tennis. Suddenly, a call comes on the telephone, and B leaves the room to pick up the call. What is C doing?

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TooCasToo@reddit

Now, just modify it so it's fully internet integrated and so it can self rewrite its own code... etc... etc.. :D

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EmiyaBoi@reddit

Can someone confirm how viable it is for tool calling? Llama 3.2 3B wasnt as good as i had hoped it would be.

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Amgadoz@reddit

You can't compare a 14B to a 3B.

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swiftninja_@reddit

What are the prompt instructions/template again?

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matteogeniaccio@reddit (OP)

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curiousily_@reddit

I've tested Phi-4 (14B) in Ollama (GGUF). - Works well on base M3 pro machine - Better than Phi-3 - Much improved instruction following Full video: https://www.youtube.com/watch?v=OcZSS37SUCE

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namankhator@reddit

I'm using the q8 on M4 Pro (24 GB), and it is pretty good.!! My use case is actually very simple: I want to ask general questions about implementing things on AWS or a new tech I do not know about. Usually use hugging chat / ChatGPT (till the free quote runs up). Thanks.!

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namankhator@reddit

PS, Getting roughly 12t/s

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BlueSwordM@reddit

Ok, I might have been wrong from my last post on the subject on phi4 lmao. Its multilingual performance is so much better than phi3. phi3 was as dumb as a rock in this domain by comparison. Now, is it better than Gemma2 9B and Qwen 2.5-14B across the board? Doesn't seem like it currently with my small set of multilingual and encoding knowledge+reasoning benchmarks, but it's close. Instruction following is still iffy: I can tell the output has just been cleansed a lot, but it's still quite a bit better than phi3. I still remember when I thought phi3 was good.

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qsta999@reddit

Phi3 was trained on only english dataset so it is expected to suck at other languages. Phi3.5 does have multilingual support for tier one languages

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Existing_Freedom_342@reddit

What?? Please delete this. How absurd! Never the Phi-4 is better than any Gemma model in multilingual. Not even Gemma 2 2B.

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TurpentineEnjoyer@reddit

Seems mediocre to bad at spatial/situational awareness, for those looking for entertainment purposes. A standard scenario I use to test it is one character entering their private quarters with luggage, and the AI character can respond as they please. More often than not it made no attempt to interpret any valid context on its turn, either based on the situation or the lore, and just started talking about other things.

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skrshawk@reddit

Almost think MS makes it that way on purpose. Contrast with Llama which might have some RP training given how readily it will play the part of a character if you tell it to.

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lostinthellama@reddit

They do. If you read the paper and look at the data it is being trained on, none fits these kinds of use cases. They are reasoning models designed for single turn interactions. Llama is trained to be good at that specifically for Meta’s character studio.

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TurpentineEnjoyer@reddit

I suspect you're right. It's not even so much just the roleplay aspect, but the situational awareness out of any special context. I test models using loose roleplay situations to feel out their capabilities and limits. (Nothing too taxing like wizards or bombastic personalities) Mistral Small is the only one I can fit on a 3090 so far that's been able to really hold its own there. This new Phi is particularly bad for it. Stuff that happened independently, minimal context given to let the LLM interpret freely: John walks into his bedroom and sighs. Alice watches him from a rooftop at the other end of the courtyard, then talks to him in speaking volume. Alice walks into the bathroom. John walks into the kitchen. Alice and John now stand in the kitchen arguing about John following Alice into the bathroom. John enters the barracks, ready to serve his country. Alice goes on a 300 word rant about restaurants in New York.

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Admirable-Star7088@reddit

I usually "benchmark" models in a similar way too, but they are a bit more complex. For example, my prompt may look something like: *"A T-1000 Terminator materializes in the Star Wars universe, specifically on the planet Tatooine. It's programmed with one mission: terminate Darth Sidious, the Emperor. Describe how this most likely will unfold. Be as logical, factual and unbiased as possible to determine the most likely outcome."* This pushes a models logical thinking, character weaknesses/strengths, situational awareness, positioning, knowledge etc to the max. A good model usually describes how the T-1000 Terminator needs to first adopt to Tatooine and gather intelligence on Darth Sidious' warebouts by infiltrating Imperial forces, which then leads to the T-1000 stealing or taking a spaceship by force from locals using its incredible strength, then travel to the planet Coruscant (where Sidious is likely to be), and then infiltrate the city, etc etc. This is a fun way to test a models capabilities. I have noted though only 70b+ models can give a really good layout with all the logical steps (with 30b models usually struggling, but they can sort of do it).

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Significant_Truth867@reddit

Like any other model, this one failed to create a simple Tetris implementation. In all cases, I use two queries. First: """ Create a plan to create a simple Tetris implementation. Requirements: \- One file \- CSS \- HTML \- JS \- Button for start \- Button for restart Just send me the plan """ Second: "" Now send me a full code according to your plan """ I tested: QwQ, Qwen 2.5 Coder 7B, Qwen 2.5 Coder 14B, Qwen 2.5 Coder 32B, Exaone 7.8B, Exaone 32B, Llama 3.1 8B, Intellect-1. Not a single model could write Tetris.

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-Ellary-@reddit

I've done tetris with Qwen 2.5 Coder 7b, Mistral Large 2, DeepSeek 2.5 - JS + HTML + CSS.

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Significant_Truth867@reddit

Share your prompt please

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__bee_07@reddit

Quick question - is there a way to download model files and load them in an environment where I cannot access these files via web (think of it as an edge device that have restricted access to internet)?

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AsliReddington@reddit

Just use a docker image for TGI or SGLANG & simply start the container in FP8 by pointing to the downloaded weights path

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matteogeniaccio@reddit (OP)

This is a fully local model. You can download it on a usb drive and move it anywhere. To run the model you need a gguf compatible app, for example lm studio

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AsliReddington@reddit

I'll stick to NSFW capable models & not this neutered ones. Mistral, Mixtral, CommandR, Nemotron etc

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Aplakka@reddit

Thanks for uploading these. Looks promising based on a few quick tests. What kind of generation parameters do people use when testing new models? E.g. temperature, min\_p, repetition penalty? I always have difficulty figuring out what to use, and usually end up using some semi-random default presets, unless there's something specifically mentioned e.g. in the model card.

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random_guy00214@reddit

See here https://www.reddit.com/r/LocalLLaMA/comments/17vonjo/your_settings_are_probably_hurting_your_model_why/

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pumukidelfuturo@reddit

i hate the gptisms on this. Back to gemma2 9b wpo.

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DhairyaRaj13@reddit

How much ram does it take to run ???

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fairydreaming@reddit

I created [llama.cpp PR](https://github.com/ggerganov/llama.cpp/pull/10817) with some Phi-4-related fixes in case anyone is interested.

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pet2pet1982@reddit

Thanks a lot! Will OpenAI compatible endpoint work? I mean at http server, path /v1/chat/completions? I need a predefined context like “You are a Senior C++ programmer” or so. Not necessarily a programmer, just “your are some pro specialist in a some quite narrow field of knowledge”.

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Admirable-Star7088@reddit

Is the output quality from Phi-4 degraded with the current version of llama.cpp?

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fairydreaming@reddit

I don't think so, it's more about avoiding the need to manually modify the model config.json file and the conversion script prior to the GGUF conversion.

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Admirable-Star7088@reddit

I see, ty for reply!

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adamavfc@reddit

ollama run [hf.co/matteogeniaccio/phi-4](http://hf.co/matteogeniaccio/phi-4)

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ArakiSatoshi@reddit

Honestly, I won't even bother testing it. I have very high doubts they had even a single internal conversation about making Phi a general-purpose model instead of a safety ambassador model.

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matteogeniaccio@reddit (OP)

It's not completely their fault. Phi4 was trained primarily from synthetic data generated by another model (probably chatGPT). My guess is that they couldn't ask the teacher model to produce unsafe training data.

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hapliniste@reddit

Do you really think ms of all people would train it on erp even if they could?

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Thellton@reddit

I'm sure they could train it on Enterprise Resource Planning... it was Enterprise Resource Planning you were talking about... right... :P

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Mescallan@reddit

It's meant for business solutions not consumers. It's pretty terrible for chatting and in business you need to reduce the chance of it talking about anime titties as low as possible.

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Sabin_Stargem@reddit

Presenter: "Our business model is to sell ads featuring pretty ladies to showcase our bras. Phi, show the boardroom some breasts clad in our wares." Phi: *presents chicken breast pieces, wrapped in bras.* Presenter: "..."

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stevelon_mobs@reddit

Doing the lord's work! u/matteogeniaccio we get a Q4\_K\_M quant too?

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matteogeniaccio@reddit (OP)

I stopped uploading quants because I'm uploading the original model from Azure. It's taking ages. I'll upload the Q4\_K\_M once the previous upload is complete.

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Portanna@reddit

Could you also add 2 bit quants for the gpu poor crowd?

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matteogeniaccio@reddit (OP)

Sorry, I'm currently traveling and I can't upload any more quants. But hopefully I can summon u/noneabove1182 for you

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TheTerrasque@reddit

Sorry to ask, but could you give sha512 for the files? Or is there a way to see that on huggingface? My download got interrupted and I want to make sure it's not corrupted.

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AXYZE8@reddit

Just click on filename on HuggingFace to see SHA256 For example Q4_K_M https://huggingface.co/matteogeniaccio/phi-4/blob/main/phi-4-Q4_K_M.gguf SHA256: 6e41c39f4490a9e8b7a65916425c6ed97f04ed95bab991c4ab6a462ff84d1608

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IAmScrewedAMA@reddit

My GPU VRAM is 16GB and I noticed the Q8 size is 15.6GB. Can I offload the whole thing into my GPU VRAM (which seems to be the case) or am I missing something here?

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aseichter2007@reddit

Maybe with like 200 tokens of context. Get the Q6.

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SomeOddCodeGuy@reddit

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aseichter2007@reddit

That's closer to modified llama 3 instruct...

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Thrumpwart@reddit

SO MANY OBVIOUS MICROSOFT BOTS AND SHILLS IN HERE OMG I KNEW IT I AM SO SMART AAAAGGGHHHHHH!

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CSharpSauce@reddit

This model is actually really good. Tested some healthcare knowledge, and it did super well.

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Born_Fox6153@reddit

PHI4 is a BEAST !!

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scientiaetlabor@reddit

Thank you!

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a_slay_nub@reddit

https://preview.redd.it/xsg2dcav7n6e1.png?width=1563&format=png&auto=webp&s=16355ae9533d129d797603f65fb31952a1f7b5c7 I swear, Microsft is trying to prove a point with these new models. They can beat benchmarks but they can't do literally anything else.

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matteogeniaccio@reddit (OP)

In llama.cpp you have to manually multiply the context size by the number in -np. For example, to set the context to 16k with np4 the command line contains: -c 65536 -np 4

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a_slay_nub@reddit

Oh, I wasn't setting -c and had -np set to 16. I'm assuming that means that every time my conversation went over 1k tokens, it was out of the max context length and that's why it was going insane.

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hapliniste@reddit

Bro every model do this if you put a bad repetition penalty and then continue the conv after they write insane shit. But yeah it's not trained in multi message chains so as a chat assistant it will likely be quite bad.

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a_slay_nub@reddit

These are with the standard settings, it should be fine. I haven't had a single other model in 2024 that has had this problem.

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mrskeptical00@reddit

Seems to be working fine for me.

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custodiam99@reddit

Very nice model for it's site.

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TheActualStudy@reddit

config.json says 16K context? Is there a bigger context version coming?

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Existing_Freedom_342@reddit

Another rubbish from MS, showing that it won't stop being dependent on "Open"AI any time soon 😂

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DarkArtsMastery@reddit

Works like a charm, just tested Q4\_K\_M in LM Studio via AMD ROCm. Fits perfectly in full 16K context on a 16GB GPU, leaving roughly 1.5GB free left in this quant. Preliminary testing looks really nice, outputs are rather conscise, but very well structured and informative. It feels surprisingly smart considering it is "only" 14B model. I get \~ 36 T/s on my RX6800XT and I'd love to see some coding fine-tunes based on this exact model. And I'd also love to see direct comparison with Qwen 2.5 14B!

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carnyzzle@reddit

That was quick

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SquashFront1303@reddit

How to glhf chat?

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a_slay_nub@reddit

general.architecture phi3 They haven't actually released it yet. They said they'd release it next week.

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SmashShock@reddit

Careful that `tid` parameter is leaking your academic instituion, it can be removed safely: https://ai.azure.com/explore/models/Phi-4/version/1/registry/azureml#artifacts

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matteogeniaccio@reddit (OP)

I downloaded it from Azure AI Foundry and converted to GGUF. This is the real Phi-4 but of course it's not an official release.

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a_slay_nub@reddit

Well that's just weird. They release the weights for you to download but not really.

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petercooper@reddit

Fantastic! Just grabbed the Q8 with LM Studio and it's running well for me. Not feeling much difference to Phi 3.5 in my initial prompts but will try and stretch its legs a bit more next..

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GeorgiaWitness1@reddit

I think i will test this extensively on my project [ExtractThinker](https://github.com/enoch3712/ExtractThinker). Even with a q8 can pull of must of the tricky load

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