What are the hardware requirements for Smaugredq?

Smaugredq requires approximately 4.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Smaugredq and how large is it?

Smaugredq is developed by Daemontatox, a model with 8b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Smaugredq perform on standard benchmarks?

Smaugredq has the following published scores: MMLU 65.77. Compare against reference models on this page or on the LLM Explorer leaderboards.

Smaugredq by Daemontatox — VRAM 4.9GB

Name: Smaugredq
Author: Daemontatox

Smaugredq is an open-source language model by Daemontatox. Features: 8b LLM, VRAM: 4.9GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.15, Arc: 59.6, HellaSwag: 80, MMLU: 65.8, GSM8K: 55.9.

Base model:abacusai/llama-3-sm... Base model:quantized:abacusai/... En Endpoints compatible Gguf Llama Quantized Region:us Unsloth

Model Card on HF 🤗: https://huggingface.co/Daemontatox/smaugredq

Smaugredq Parameters and Internals

LLM Name	Smaugredq
Repository 🤗	https://huggingface.co/Daemontatox/smaugredq
Base Model(s)	Llama 3 Smaug 8B abacusai/Llama-3-Smaug-8B
Model Size	8b
Required VRAM	4.9 GB
Updated	2024-08-11
Maintainer	Daemontatox
Model Type	llama
Model Files	16.1 GB 4.9 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel
License	apache-2.0

Rank the Smaugredq capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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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Note: green Score (e.g. "73.2") means that the model is better than Daemontatox/smaugredq.