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Mistral "Mixtral" 8x7B 32k model [magnet]

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Re: Mistral "Mixtral" 8x7B 32k model [magnet]

#4
Looks to be Mixture of Experts, here is the params.json:

    {
        "dim": 4096,
        "n_layers": 32,
        "head_dim": 128,
        "hidden_dim": 14336,
        "n_heads": 32,
        "n_kv_heads": 8,
        "norm_eps": 1e-05,
        "vocab_size": 32000,
        "moe": {
            "num_experts_per_tok": 2,
            "num_experts": 8
        }
    }

Re: Mistral "Mixtral" 8x7B 32k model [magnet]

#8

Honest question: Why isn't this on Huggingface? Is this one a leaked model with a questionable training or alignment methodology? EDIT: I mean, I guess they didn't hack their own twitter account, but still.

It'll be on Huggingface soon. This is how they dropped their original 7B model as well. It's a marketing thing, but it works!

Re: Mistral "Mixtral" 8x7B 32k model [magnet]

#9
post #8

Honest question: Why isn't this on Huggingface? Is this one a leaked model with a questionable training or alignment methodology? EDIT: I mean, I guess they didn't hack their own twitter account, but still.

It'll be on Huggingface soon. This is how they dropped their original 7B model as well. It's a marketing thing, but it works!

Ah, well, ok. I appreciate the torrent link -- much faster distribution.

Re: Mistral "Mixtral" 8x7B 32k model [magnet]

#10
post #6

No public statement from Mistral yet. What we know: - Mixture of Experts architecture. - 8x 7B parameters experts (potentially trained starting with their base 7B model?). - 96GB of weights. You won't be able to run this on your home GPU.

Theoretically it could fit into a single 24GB GPU if 4-bit quantized. Exllama v2 has even more efficient quantization algorithm, and was able to fit 70B models in 24GB gpu, but only with 2048 tokens of context.
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