What are the hardware requirements for Trocr Bigram5 BY?

Trocr Bigram5 BY requires approximately 1.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Trocr Bigram5 BY and how large is it?

Trocr Bigram5 BY is developed by cyttic, a model with 299.5m 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 Trocr Bigram5 BY?

Trocr Bigram5 BY is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Trocr Bigram5 BY by cyttic — VRAM 1.2GB

Name: Trocr Bigram5 BY
Author: cyttic

Trocr Bigram5 BY is an open-source language model by cyttic. Features: 299.5m LLM, VRAM: 1.2GB, LLM Explorer Score: 0.3.

Base model:cyttic/exp2-frozen-... Base model:finetune:cyttic/exp... Endpoints compatible Generated from trainer Image-text-to-text Region:us Safetensors Vision Vision-encoder-decoder

Model Card on HF 🤗: https://huggingface.co/cyttic/trocr-bigram5-BY

Trocr Bigram5 BY Parameters and Internals

LLM Name	Trocr Bigram5 BY
Repository 🤗	https://huggingface.co/cyttic/trocr-bigram5-BY
Base Model(s)	cyttic/exp2-frozen-benyehuda-cont cyttic/exp2-frozen-benyehuda-cont
Model Size	299.5m
Required VRAM	1.2 GB
Updated	2026-09-05
Maintainer	cyttic
Model Type	vision-encoder-decoder
Model Files	1.2 GB 0.0 GB
Model Architecture	VisionEncoderDecoderModel
Model Max Length	512
Transformers Version	5.15.0
Tokenizer Class	TokenizersBackend
Padding Token	[PAD]
Vocabulary Size	128000

Rank the Trocr Bigram5 BY 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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