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Firefly Mixtral 8x7b AWQ by TheBloke

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  4-bit   Autotrain compatible   Awq Base model:quantized:yeungnlp/... Base model:yeungnlp/firefly-mi...   En   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/TheBloke/firefly-mixtral-8x7b-AWQ 

Firefly Mixtral 8x7b AWQ Benchmarks

LLME Score: 0.1302
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Firefly Mixtral 8x7b AWQ (TheBloke/firefly-mixtral-8x7b-AWQ)
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Firefly Mixtral 8x7b AWQ Parameters and Internals

Model Type 
mixtral
Additional Notes 
AWQ is used for efficient 4-bit quantization. Models are compatible with various systems like text-generation-webui, Transformers, and vLLM.
Supported Languages 
en (high)
Input Output 
Input Format:
[INST] {prompt} [/INST]
Accepted Modalities:
text
Output Format:
text
Performance Tips:
Installing latest versions of dependencies improves performance.
LLM NameFirefly Mixtral 8x7b AWQ
Repository 🤗https://huggingface.co/TheBloke/firefly-mixtral-8x7b-AWQ 
Model NameFirefly Mixtral 8X7B
Model CreatorYeungNLP
Base Model(s)  Firefly Mixtral 8x7b   YeungNLP/firefly-mixtral-8x7b
Model Size6.5b
Required VRAM24.7 GB
Updated2025-08-25
MaintainerTheBloke
Model Typemixtral
Model Files  10.0 GB: 1-of-3   10.0 GB: 2-of-3   4.7 GB: 3-of-3
Supported Languagesen
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/firefly-mixtral-8x7b-AWQ.

Rank the Firefly Mixtral 8x7b AWQ Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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