exploring_the_hugging_face_platform.py

# -*- coding: utf-8 -*-
"""Exploring the Hugging Face Platform.ipynb

Automatically generated by Colab.

Original file is located at
    https://colab.research.google.com/drive/1fsc-c8TTjqQvV2txQDrSJ5bp8p2suPIZ

**Using the Access Token**
"""

from huggingface_hub import login
# Replace 'your-access-token' with your actual Hugging Face access token
login(token="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")

"""## **Testing the Setup**"""

from transformers import AutoModelForMaskedLM, AutoTokenizer, pipeline

# Load the pre-trained model and tokenizer from Hugging Face
model_name = "bert-base-uncased"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForMaskedLM.from_pretrained(model_name)

# Create a pipeline for masked language modeling
nlp_pipeline = pipeline("fill-mask", model=model, tokenizer=tokenizer)

# Test the pipeline with a simple input
test_sentence = "The quick brown fox jumps over the [MASK] dog."
result = nlp_pipeline(test_sentence)

print(result)

test_sentence1 = "I am coming to your [MASK] to eat along with you."
result1 = nlp_pipeline(test_sentence1)

print(result1)