t5_small_skill_loc

T5 Small - Skill & Location Extractor

This model extracts skills and location from job descriptions using T5.

🧠 Model Details

• Base model: t5-base
• Task: Sequence-to-sequence (text-to-text)
• Training data: Custom dataset of job descriptions
• Trained to output:
  skills: <skills>, location: <location>

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🚀 How to Use

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import torch

model_name = "arhansd1/t5_small_skill_loc"
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name).to(device)

def extract_skills_and_location(job_description):
    input_text = "Extract skills and location: " + job_description
    inputs = tokenizer(input_text, return_tensors="pt", truncation=True, max_length=512).to(device)

    with torch.no_grad():
        outputs = model.generate(inputs.input_ids, max_length=128, num_beams=4, early_stopping=True)

    return tokenizer.decode(outputs[0], skip_special_tokens=True)

# 🔍 Example
sample = "Enter a sample description"
print(extract_skills_and_location(sample))