What are the hardware requirements for Griffin 1024 Llama3t 8layer Simplewiki Silu?

Griffin 1024 Llama3t 8layer Simplewiki Silu requires approximately 0.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Griffin 1024 Llama3t 8layer Simplewiki Silu and how large is it?

Griffin 1024 Llama3t 8layer Simplewiki Silu is developed by pszemraj, a model with 233.7m parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Griffin 1024 Llama3t 8layer Simplewiki Silu?

Griffin 1024 Llama3t 8layer Simplewiki Silu is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Griffin 1024 Llama3t 8layer Simplewiki Silu by pszemraj — VRAM 0.9GB

Name: Griffin 1024 Llama3t 8layer Simplewiki Silu
Author: pszemraj

Griffin 1024 Llama3t 8layer Simplewiki Silu is an open-source language model by pszemraj. Features: 233.7m LLM, VRAM: 0.9GB, License: apache-2.0, LLM Explorer Score: 0.12.

Dataset:pszemraj/simple wikipe... En Endpoints compatible Generated from trainer Recurrent gemma Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/pszemraj/griffin-1024-llama3t-8layer-simplewiki-silu

Griffin 1024 Llama3t 8layer Simplewiki Silu Parameters and Internals

Supported Languages

en (primary)

Training Details

Data Sources:

pszemraj/simple_wikipedia_LM

LLM Name	Griffin 1024 Llama3t 8layer Simplewiki Silu
Repository 🤗	https://huggingface.co/pszemraj/griffin-1024-llama3t-8layer-simplewiki-silu
Model Size	233.7m
Required VRAM	0.9 GB
Updated	2026-07-29
Maintainer	pszemraj
Model Type	recurrent_gemma
Model Files	0.9 GB 0.0 GB
Supported Languages	en
Model Architecture	RecurrentGemmaForCausalLM
License	apache-2.0
Transformers Version	4.40.1
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	128256
Torch Data Type	float32

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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