Text Classification
Transformers
PyTorch
Arabic
English
distilbert
chemistry
biology
finance
legal
music
code
art
climate
medical
emotion
endpoints-template
Instructions to use PetraAI/Zalmati with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PetraAI/Zalmati with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="PetraAI/Zalmati")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("PetraAI/Zalmati") model = AutoModelForSequenceClassification.from_pretrained("PetraAI/Zalmati") - Notebooks
- Google Colab
- Kaggle
| import streamlit as st | |
| import gradio as gr | |
| def greet(name): | |
| return "Hello " + name + "!!" | |
| iface = gr.Interface(fn=greet, inputs="text", outputs="text") | |
| iface.launch() | |
| x = st.slider('Select a value') | |
| st.write(x, 'squared is', x * x) | |