What are the hardware requirements for Emoopt 13B?

Emoopt 13B requires approximately 25.7 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 Emoopt 13B and how large is it?

Emoopt 13B is developed by lzw1008, a model with 13b 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 Emoopt 13B?

Emoopt 13B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Emoopt 13B by lzw1008 — VRAM 25.7GB, 2K context

Name: Emoopt 13B
Author: lzw1008

Emoopt 13B is an open-source language model by lzw1008. Features: 13b LLM, VRAM: 25.7GB, Context: 2K, License: mit, LLM Explorer Score: 0.11.

Arxiv:2401.08508 En Endpoints compatible Opt Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/lzw1008/Emoopt-13b

Emoopt 13B Parameters and Internals

Model Type

affective analysis, instruction-following

Use Cases

Areas:

Affective analysis

Applications:

Sentimental polarity classification, Categorical emotions classification, Sentiment strength regression, Emotion intensity regression

Primary Use Cases:

Affective classification, Sentiment analysis

Limitations:

Challenges in application due to bias and over-generalization

Considerations:

Adjust task description according to specific task.

Supported Languages

en (English)

Training Details

Data Sources:

AAID instruction tuning data

Methodology:

Finetuning

Model Architecture:

Finetuned based on OPT-13B

Safety Evaluation

Risk Categories:

potential bias, incorrect predictions, over-generalization

Ethical Considerations:

Potential bias and over-generalization illustrated as possible risks.

Responsible Ai Considerations

Fairness:

Bias such as gender gaps indicated.

Mitigation Strategies:

Challenges acknowledged in applying in real-world scenarios.

Input Output

Accepted Modalities:

text

LLM Name	Emoopt 13B
Repository 🤗	https://huggingface.co/lzw1008/Emoopt-13b
Model Size	13b
Required VRAM	25.7 GB
Updated	2026-06-03
Maintainer	lzw1008
Model Type	opt
Model Files	5.0 GB: 1-of-6 5.0 GB: 2-of-6 4.8 GB: 3-of-6 4.8 GB: 4-of-6 5.0 GB: 5-of-6 1.1 GB: 6-of-6
Supported Languages	en
Model Architecture	OPTForCausalLM
License	mit
Context Length	2048
Model Max Length	2048
Transformers Version	4.36.1
Tokenizer Class	GPT2Tokenizer
Padding Token	<s>
Vocabulary Size	50272
Torch Data Type	float16
Activation Function	relu
Errors	replace

Rank the Emoopt 13B 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 Emoopt 13B

Best Alternatives	Context / RAM	Downloads	Likes
OPT 13B Nerybus Mix	2K / 26.4 GB	171	36
Opt 13B	2K / 25.8 GB	11924	65
OPT 13B Erebus	2K / 25.7 GB	413	261
OPT 13B Nerys V2	2K / 25.7 GB	110	12
Basic Facebook 13B	2K / 25.8 GB	15	1
Opt 13B	2K / 26.3 GB	7	1
OPT 13B Nerybus Mix 4bit 128g	2K / 7.3 GB	58	6
OPT 13B Erebus 4bit 128g	2K / 7.3 GB	8	17