Smaug 34B V0.1 AWQ by LoneStriker

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  4-bit   Autotrain compatible   Awq Base model:jondurbin/bagel-34b... Base model:quantized:jondurbin...   Conversational   Endpoints compatible   Llama   Quantized   Region:us   Safetensors   Sharded   Tensorflow

Smaug 34B V0.1 AWQ Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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Smaug 34B V0.1 AWQ Parameters and Internals

Additional Notes 
This model is a finetune of jondurbin's bagel model, trained with new datasets and a new technique to be shared soon. There is no merging.
LLM NameSmaug 34B V0.1 AWQ
Repository ๐Ÿค—https://huggingface.co/LoneStriker/Smaug-34B-v0.1-AWQ 
Base Model(s)  jondurbin/bagel-34b-v0.2   jondurbin/bagel-34b-v0.2
Model Size34b
Required VRAM19.2 GB
Updated2024-12-03
MaintainerLoneStriker
Model Typellama
Model Files  5.0 GB: 1-of-4   5.0 GB: 2-of-4   4.9 GB: 3-of-4   4.3 GB: 4-of-4
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length200000
Model Max Length200000
Transformers Version4.37.1
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size64000
Torch Data Typefloat16
Smaug 34B V0.1 AWQ (LoneStriker/Smaug-34B-v0.1-AWQ)

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Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/Smaug-34B-v0.1-AWQ.

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124