can you give me a tuotrial on using models on huggingface?

Sure! Here's a step-by-step tutorial on using models on Hugging Face:

1. Install the Transformers library:

!pip install transformers

2. Import the necessary libraries:

from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline

3. Choose a pre-trained model from the Hugging Face model hub. For this tutorial, we'll use the DistilBERT model for sentiment analysis:

model_name = "distilbert-base-uncased-finetuned-sst-2-english"

4. Load the tokenizer and model:

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

5. Create a pipeline for sentiment analysis:

sentiment_pipeline = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer)

6. Use the pipeline to analyze some text:

text = "I loved the new movie, it was amazing!"
result = sentiment_pipeline(text)
print(result)

This should output:

[{'label': 'POSITIVE', 'score': 0.9998785252571106}]

And that's it! You can now use Hugging Face to quickly and easily use pre-trained models for various NLP tasks.