| import gradio as gr | |
| # from transformers import pipeline | |
| def greet(name): | |
| return "Hello " + name + "!!" | |
| # classifier = pipeline("sentiment-analysis") | |
| # classifier( | |
| # [ | |
| # "I've been waiting for a HuggingFace course my whole life.", | |
| # "I hate this so much!", | |
| # ] | |
| # ) | |
| iface = gr.Interface(fn=greet, inputs="text", outputs="text") | |
| iface.launch() | |
| # import torch | |
| # from transformers import AutoTokenizer, AutoModelForSequenceClassification | |
| # checkpoint = "distilbert-base-uncased-finetuned-sst-2-english" | |
| # tokenizer = AutoTokenizer.from_pretrained(checkpoint) | |
| # model = AutoModelForSequenceClassification.from_pretrained(checkpoint) | |
| # sequences = ["I've been waiting for a HuggingFace course my whole life.", "So have I!"] | |
| # tokens = tokenizer(sequences, padding=True, truncation=True, return_tensors="pt") | |
| # output = model(**tokens) |