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Instruct Mixtral 8x7B V0.1 Dolly15K AWQ by TheBloke

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Instruct Mixtral 8x7B V0.1 Dolly15K AWQ is an open-source language model by TheBloke. Features: 46.7b LLM, VRAM: 24.7GB, Context: 32K, License: apache-2.0, MoE, Quantized, Instruction-Based, LLM Explorer Score: 0.11.

  4-bit   Awq Base model:brillibits/instruct... Base model:quantized:brillibit...   Conversational Dataset:databricks/databricks-...   Instruct   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/TheBloke/Instruct_Mixtral-8x7B-v0.1_Dolly15K-AWQ 

Instruct Mixtral 8x7B V0.1 Dolly15K AWQ Benchmarks

LLME Score: 0.10983
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Instruct Mixtral 8x7B V0.1 Dolly15K AWQ (TheBloke/Instruct_Mixtral-8x7B-v0.1_Dolly15K-AWQ)
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Instruct Mixtral 8x7B V0.1 Dolly15K AWQ Parameters and Internals

Model Type 
mixtral
Additional Notes 
The model offers efficient, accurate, and fast low-bit weight quantization methods with AWQ, specifically supporting 4-bit quantization.
Supported Languages 
English (fluent)
Training Details 
Data Sources:
databricks/databricks-dolly-15k
Methodology:
Fine-tuned using QLora
Context Length:
1024
Training Time:
1.0 epochs
Model Architecture:
Llama 2 transformer architecture
Input Output 
Input Format:
{prompt} Output:
Accepted Modalities:
text
Output Format:
Text generation output
Release Notes 
Version:
0.1
Notes:
Initial release of Instruct Mixtral 8X7B V0.1 Dolly15K.
LLM NameInstruct Mixtral 8x7B V0.1 Dolly15K AWQ
Repository 🤗https://huggingface.co/TheBloke/Instruct_Mixtral-8x7B-v0.1_Dolly15K-AWQ 
Model NameInstruct Mixtral 8X7B V0.1 Dolly15K
Model CreatorBrillibits
Base Model(s)  Brillibits/Instruct_Mixtral-8x7B-v0.1_Dolly15K   Brillibits/Instruct_Mixtral-8x7B-v0.1_Dolly15K
Model Size46.7b
Required VRAM24.7 GB
Updated2026-04-21
MaintainerTheBloke
Model Typemixtral
Instruction-BasedYes
Model Files  10.0 GB: 1-of-3   10.0 GB: 2-of-3   4.7 GB: 3-of-3
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Instruct_Mixtral-8x7B-v0.1_Dolly15K-AWQ.

Rank the Instruct Mixtral 8x7B V0.1 Dolly15K AWQ Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

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