Emoji Suggester

This model is a text generation model that can suggest emojis based on a given text. It uses the deberta-v3-base model as a backbone.

Training Data

The dataset this was trained on has had it's emoji's replaced with the unicode characters rather than an index, which required a seperate file to map the indices to. The dataset was further modified in the following ways:

The "US" emoji was removed, as it serves very little purpose in general conversation.
The dataset was deduped
The amount of times each emoji appears in the dataset is more or less even to all the others; preventing the model from becoming heavily biased on the emojis that appear more often in training data.

Intended uses & limitations

This model is intended to be used for fun and entertainment purposes, such as adding emojis to social media posts, messages, or emails. It is not intended to be used for any serious or sensitive applications, such as sentiment analysis, emotion recognition, or hate speech detection. The model may not be able to handle texts that are too long, complex, or ambiguous, and may generate inappropriate or irrelevant emojis in some cases. The model may also reflect the biases and stereotypes present in the training data, such as gender, race, or culture. Users are advised to use the model with caution and discretion.

Model Training Info

Problem type: Multi-class Classification
CO2 Emissions (in grams): 0.6834

Validation Metrics

Loss: 2.339
Accuracy: 0.216
Macro F1: 0.136
Micro F1: 0.216
Weighted F1: 0.163
Macro Precision: 0.126
Micro Precision: 0.216
Weighted Precision: 0.152
Macro Recall: 0.179
Micro Recall: 0.216
Weighted Recall: 0.216

Usage

You can use cURL to access this model:

$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love apples"}' https://api-inference.huggingface.co/models/KoalaAI/Emoji-Suggester

Or Python API:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("KoalaAI/Emoji-Suggester", use_auth_token=True)

tokenizer = AutoTokenizer.from_pretrained("KoalaAI/Emoji-Suggester", use_auth_token=True)

inputs = tokenizer("I love AutoTrain", return_tensors="pt")

outputs = model(**inputs)

KoalaAI
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Emoji-Suggester