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Synthia MoE V3 Mixtral 8x7B 3.5bpw H6 EXL2 2 by LoneStriker

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  Autotrain compatible   Endpoints compatible   Exl2   Mixtral   Moe   Pytorch   Quantized   Region:us   Sharded   Tensorflow

Synthia MoE V3 Mixtral 8x7B 3.5bpw H6 EXL2 2 Parameters and Internals

LLM NameSynthia MoE V3 Mixtral 8x7B 3.5bpw H6 EXL2 2
RepositoryOpen on 🤗 
Required VRAM20.7 GB
Updated2024-07-27
MaintainerLoneStriker
Model Typemixtral
Model Files  8.6 GB: 1-of-3   8.6 GB: 2-of-3   3.5 GB: 3-of-3
Quantization Typeexl2
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typebfloat16
Synthia MoE V3 Mixtral 8x7B 3.5bpw H6 EXL2 2 (LoneStriker/Synthia-MoE-v3-Mixtral-8x7B-3.5bpw-h6-exl2-2)

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...B Instruct V0.1 8.0bpw H8 EXL20.264K / 120.2 GB141
...M 2 8x22B Beige 2.4bpw H6 EXL20.264K / 42.7 GB100
...M 2 8x22B Beige 5.0bpw H6 EXL20.264K / 88.5 GB100
...2 Mixtral 8x22b 8.0bpw H8 EXL20.264K / 125.1 GB112
...rdLM 2 8x22B Beige EXL2 5.0bpw0.264K / 88.4 GB70
Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/Synthia-MoE-v3-Mixtral-8x7B-3.5bpw-h6-exl2-2.

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024072501
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