What are the hardware requirements for Opt 350M Email Generation?

Opt 350M Email Generation requires approximately 1.3 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 Email Generation and how large is it?

Opt 350M Email Generation 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 Email Generation?

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

Opt 350M Email Generation by pszemraj — VRAM 1.3GB, 2K context

Name: Opt 350M Email Generation
Author: pszemraj

Opt 350M Email Generation is an open-source language model by pszemraj. Features: 350m LLM, VRAM: 1.3GB, Context: 2K, License: other, LLM Explorer Score: 0.01.

Auto-complete Dataset:aeslc Email Endpoints compatible Generated from trainer Non-commercial Opt Pytorch Region:us Safetensors

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

Opt 350M Email Generation Parameters and Internals

Model Type

text generation

Use Cases

Areas:

research, commercial applications

Applications:

email automation

Primary Use Cases:

email completion and generation

Limitations:

Restricted to generating 64 tokens, Formatting significantly affects results

Additional Notes

Please refer to the license and usage guidelines on the Hugging Face model card for specific usage terms.

Training Details

Data Sources:

aeslc

Methodology:

fine-tuning

Input Output

Input Format:

Emails

Accepted Modalities:

text

Output Format:

Completed/email text

Performance Tips:

Formatting matters, significant variance possible.

LLM Name	Opt 350M Email Generation
Repository 🤗	https://huggingface.co/pszemraj/opt-350m-email-generation
Model Size	350m
Required VRAM	1.3 GB
Updated	2026-05-12
Maintainer	pszemraj
Model Type	opt
Model Files	1.3 GB 1.3 GB 0.0 GB
Model Architecture	OPTForCausalLM
License	other
Context Length	2048
Model Max Length	2048
Transformers Version	4.19.2
Tokenizer Class	GPT2Tokenizer
Beginning of Sentence Token	</s>
End of Sentence Token	</s>
Unk Token	</s>
Vocabulary Size	50265
Torch Data Type	float32
Activation Function	relu
Errors	replace

Rank the Opt 350M Email Generation 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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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
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Gpt350 Chat S V0 1	2K / 0.7 GB	5	0
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Note: green Score (e.g. "73.2") means that the model is better than pszemraj/opt-350m-email-generation.