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wolfram/miqu-1-120b
miqu-1-120b is a text generation model from wolfram. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as other.
Downloads · 30 days
62
1% of all-time downloads
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120B
241 GB on disk
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.safetensors241 GB · 100%
From the Hugging Face model README

This is a 120b frankenmerge of miqu-1-70b created by interleaving layers of miqu-1-70b-sf with itself using mergekit.
Inspired by Venus-120b-v1.2, MegaDolphin-120b, and goliath-120b.
Thanks for the support, CopilotKit - the open-source platform for building in-app AI Copilots into any product, with any LLM model. Check out their GitHub.
Thanks for the EXL2 and GGUF quants, Lone Striker!
Also available: miquliz-120b-v2.0 – Miqu's younger, fresher sister; a new and improved Goliath-like merge of Miqu and lzlv.
u/SomeOddCodeGuy wrote on r/LocalLLaMA:
I love this model. It's slow as Christmas but it's SO GOOD. You did great on this.
But this model is close to getting me to shut down my ChatGPT 4 subscription lol. Between it, Deepseek and a couple others, I'm not sure I'll be using ChatGPT much anymore.
Im using the Q8 at 16k, and I can't express how true it remains to its context. I might try to do some testing this weekend, but its great so far.
I've been using your miqu-1 the past two days and its phenomenal. It understands everything I'm saying in ways only ChatGPT did. I've been purposefully getting more and more vague/relaxed in my speaking, and talking about the most inane stuff, and it just follows right along like a person would.
Miqu-1 does ignore instructions a little. I tried to make a more sarcastic/insulting AI assistant to chat with, and specifically told it (multiple times after a few tries) to not apologize to me after, and it wouldn't stop. So if it made a jab like "Wow, great work spelling that word. Quite the whiz kid huh?", making fun of me for misspelling something, it would refuse to not follow up with "Seriously, though, sometimes misspellings happen" lol. But that's the only issue I've had with it.
(Note: All I did was merge this, though, so the credit mostly belongs to Mistral AI (giving proper attribution!) and the creators of mergekit as well as Venus-120b-v1.2 and MegaDolphin-120b who inspired it.)
<s>[INST] {prompt} [/INST]
This model was merged using the passthrough merge method.
The following models were included in the merge:
The following YAML configuration was used to produce this model:
dtype: float16
merge_method: passthrough
slices:
- sources:
- layer_range: [0, 20]
model: 152334H/miqu-1-70b-sf
- sources:
- layer_range: [10, 30]
model: 152334H/miqu-1-70b-sf
- sources:
- layer_range: [20, 40]
model: 152334H/miqu-1-70b-sf
- sources:
- layer_range: [30, 50]
model: 152334H/miqu-1-70b-sf
- sources:
- layer_range: [40, 60]
model: 152334H/miqu-1-70b-sf
- sources:
- layer_range: [50, 70]
model: 152334H/miqu-1-70b-sf
- sources:
- layer_range: [60, 80]
model: 152334H/miqu-1-70b-sf
This model contains leaked weights and due to its content it should not be used by anyone. 😜
But seriously:
What I know: Weights produced by a machine are not copyrightable so there is no copyright owner who could grant permission or a license to use, or restrict usage, once you have acquired the files.
What I believe: All generative AI, including LLMs, only exists because it is trained mostly on human data (both public domain and copyright-protected, most likely acquired without express consent) and possibly synthetic data (which is ultimately derived from human data, too). It is only fair if something that is based on everyone's knowledge and data is also freely accessible to the public, the actual creators of the underlying content. Fair use, fair AI!