Deacon 34B AWQ by TheBloke

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  4-bit   Autotrain compatible   Awq Base model:knutjaegersberg/dea... Base model:quantized:knutjaege... Dataset:totally-not-an-llm/eve...   Llama   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF ๐Ÿค—: https://huggingface.co/TheBloke/Deacon-34B-AWQ 

Deacon 34B AWQ Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Deacon 34B AWQ (TheBloke/Deacon-34B-AWQ)

Deacon 34B AWQ Parameters and Internals

Model Type 
yi
Additional Notes 
Model has been quantified using AWQ (Adaptive Weight Quantization) with hardware provided by Massed Compute.
Training Details 
Data Sources:
totally-not-an-llm/EverythingLM-data-V3
Methodology:
fine-tuned for 5 epochs with NEFTune
Model Architecture:
Llama Tokenizer compatible
Input Output 
Input Format:
### System: {system_message} ### Instruction: {prompt} ### Response:
LLM NameDeacon 34B AWQ
Repository ๐Ÿค—https://huggingface.co/TheBloke/Deacon-34B-AWQ 
Model NameDeacon 34B
Model CreatorKnut Jägersberg
Base Model(s)  Deacon 34B   KnutJaegersberg/Deacon-34B
Model Size34b
Required VRAM19.3 GB
Updated2025-02-05
MaintainerTheBloke
Model Typellama
Model Files  10.0 GB: 1-of-2   9.3 GB: 2-of-2
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length4096
Model Max Length4096
Transformers Version4.35.0
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size64000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Deacon-34B-AWQ.

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Instruction Following and Task Automation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241227