What are the hardware requirements for Opt 350M Multiprompt?

Opt 350M Multiprompt requires approximately 0.7 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Opt 350M Multiprompt and how large is it?

Opt 350M Multiprompt is developed by pszemraj, a model with 350m 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 Opt 350M Multiprompt?

Opt 350M Multiprompt is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Opt 350M Multiprompt by pszemraj — VRAM 0.7GB, 2K context

Name: Opt 350M Multiprompt
Author: pszemraj

Opt 350M Multiprompt is an open-source language model by pszemraj. Features: 350m LLM, VRAM: 0.7GB, Context: 2K, License: other, LLM Explorer Score: 0.04.

Dataset:pszemraj/text2image-mu... Endpoints compatible Generated from trainer Midjourney Opt Prompt augment Pytorch Region:us Safetensors Stable diffusion Text to image Text2image

Model Card on HF 🤗: https://huggingface.co/pszemraj/opt-350m-multiprompt

Opt 350M Multiprompt Parameters and Internals

Model Type

text generation, stable diffusion, midjourney, text2image, text to image, prompt augment, prompt engineering

Use Cases

Limitations:

The model will generate augmentations that are biased towards the training data.

Additional Notes

The model works well with any text to image tool like DALL-E 2.

Training Details

Data Sources:

pszemraj/text2image-multi-prompt, pszemraj/text2image-prompts-multi

LLM Name	Opt 350M Multiprompt
Repository 🤗	https://huggingface.co/pszemraj/opt-350m-multiprompt
Model Size	350m
Required VRAM	0.7 GB
Updated	2026-08-05
Maintainer	pszemraj
Model Type	opt
Model Files	0.7 GB 0.7 GB 0.0 GB
Model Architecture	OPTForCausalLM
License	other
Context Length	2048
Model Max Length	2048
Transformers Version	4.25.0.dev0
Tokenizer Class	GPT2Tokenizer
Beginning of Sentence Token	</s>
End of Sentence Token	</s>
Unk Token	</s>
Vocabulary Size	50272
Activation Function	relu
Errors	replace

Rank the Opt 350M Multiprompt 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

Best Alternatives to Opt 350M Multiprompt

Best Alternatives	Context / RAM	Downloads	Likes
Opt Mini Dataset 0	2K / 0.7 GB	8	0
Opt 350M	2K / 0.7 GB	198521	149
Facebook Opt 350M SFT Korz14	2K / 0.7 GB	9	0
Temp Model Sft	2K / 1.3 GB	7	0
Gpt350 Chat S V0	2K / 0.7 GB	6	0
Gpt350 Chat S V0 1	2K / 0.7 GB	5	0
Dadjokes Tuned Opt	2K / 1.3 GB	8	2
Pygmalion 350M	2K / 1.3 GB	348	54
Rockyalquimista888	2K / 1.3 GB	8	0
Remedycure	2K / 1.3 GB	6	0

Note: green Score (e.g. "73.2") means that the model is better than pszemraj/opt-350m-multiprompt.