---
language:
- en
tags:
- markdown
- information
- index
---
# Model Catalogue

[This repository](https://huggingface.co/agentlans) contains a collection of boutique AI models and is organized as follows:

## Pretrained Base Models for Text Embedding

### English Models
These models were finetuned on a subset of [Zyphra/Zyda-2](https://huggingface.co/datasets/Zyphra/Zyda-2):

- [snowflake-arctic-embed-xs-zyda-2](https://huggingface.co/agentlans/snowflake-arctic-embed-xs-zyda-2)
- [deberta-v3-xsmall-zyda-2](https://huggingface.co/agentlans/deberta-v3-xsmall-zyda-2)
- [deberta-v3-base-zyda-2](https://huggingface.co/agentlans/deberta-v3-base-zyda-2)

### Multilingual Models
These models were aligned using [agentlans/en-translations](https://huggingface.co/datasets/agentlans/en-translations):

- [multilingual-e5-small-aligned](https://huggingface.co/agentlans/multilingual-e5-small-aligned)
- [distilbert-base-multilingual-cased-aligned](https://huggingface.co/agentlans/distilbert-base-multilingual-cased-aligned)

## Text Statistics Models

These models take text as input and output a number.

| Base Model | Language | Quality | Readability | Sentiment |
|------------|----------|---------|-------------|-----------|
| deberta-v3-xsmall-zyda-2 | English | [Link](https://huggingface.co/agentlans/deberta-v3-xsmall-zyda-2-quality) | [Link](https://huggingface.co/agentlans/deberta-v3-xsmall-zyda-2-readability) | [Link](https://huggingface.co/agentlans/deberta-v3-xsmall-zyda-2-sentiment) |
| deberta-v3-base-zyda-2 | English | [Link](https://huggingface.co/agentlans/deberta-v3-base-zyda-2-quality) | [Link](https://huggingface.co/agentlans/deberta-v3-base-zyda-2-readability) | [Link](https://huggingface.co/agentlans/deberta-v3-base-zyda-2-sentiment) |
| multilingual-e5-small-aligned | Multilingual | [Link](https://huggingface.co/agentlans/multilingual-e5-small-aligned-quality) | [Link](https://huggingface.co/agentlans/multilingual-e5-small-aligned-readability) | [Link](https://huggingface.co/agentlans/multilingual-e5-small-aligned-sentiment) |
| mdeberta-v3-base | Multilingual | [Link](https://huggingface.co/agentlans/mdeberta-v3-base-quality) | [Link](https://huggingface.co/agentlans/mdeberta-v3-base-readability) | [Link](https://huggingface.co/agentlans/mdeberta-v3-base-sentiment) |

**Note:** The `mdeberta-v3-base` models were trained on a previous version of the dataset, not the complete dataset.

## Small Text-to-Text Models (English Only)

These models take text as input and produce text as output.

| Task | Model | Dataset |
|------|-------|---------|
| Keyword extraction | [flan-t5-small-keywords](https://huggingface.co/agentlans/flan-t5-small-keywords) | [wikipedia-paragraph-keywords](https://huggingface.co/datasets/agentlans/wikipedia-paragraph-keywords) |
| Title generation | [flan-t5-small-title](https://huggingface.co/agentlans/flan-t5-small-title) | [wikipedia-paragraph-titles](https://huggingface.co/datasets/agentlans/wikipedia-paragraph-titles) |
| Summarization | [text-summarization](https://huggingface.co/agentlans/text-summarization) | [wikipedia-paragraph-summaries](https://huggingface.co/datasets/agentlans/wikipedia-paragraph-summaries) |

## Natural Language Inference (NLI) Models (English Only)

These models take text as input and output a label (entailment, neutral, or contradiction).

- [all-MiniLM-L6-v2-nli](https://huggingface.co/agentlans/all-MiniLM-L6-v2-nli)
- [bge-small-en-v1.5-nli](https://huggingface.co/agentlans/bge-small-en-v1.5-nli)
- [e5-small-v2-nli](https://huggingface.co/agentlans/e5-small-v2-nli)
- [mobilebert-uncased-nli](https://huggingface.co/agentlans/mobilebert-uncased-nli)
- [NoInstruct-small-Embedding-v0-nli](https://huggingface.co/agentlans/NoInstruct-small-Embedding-v0-nli)
- [snowflake-arctic-embed-s-nli](https://huggingface.co/agentlans/snowflake-arctic-embed-s-nli)
- [snowflake-arctic-embed-xs-nli](https://huggingface.co/agentlans/snowflake-arctic-embed-xs-nli)
- [TinyBERT_General_4L_312D-nli](https://huggingface.co/agentlans/TinyBERT_General_4L_312D-nli)