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--- |
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datasets: |
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- ShashiVish/cover-letter-dataset |
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language: |
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- en |
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metrics: |
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- bleu |
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tags: |
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- text2text-generation |
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--- |
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# Usage |
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Plese find below example how to generate cover letter for input. |
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### Running the model on a GPU |
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```python |
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from transformers import T5Tokenizer, T5ForConditionalGeneration |
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tokenizer = T5Tokenizer.from_pretrained("ShashiVish/t5-base-fine-tune-1024-cover-letter") |
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model = T5ForConditionalGeneration.from_pretrained("ShashiVish/t5-base-fine-tune-1024-cover-letter" , max_length = 512 , device_map="auto") |
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job_title = "Senior Java Developer" |
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preferred_qualification = "3+ years of Java, Spring Boot" |
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hiring_company_name = "Google" |
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user_name = "Emily Evans" |
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past_working_experience= "Java Developer at XYZ for 4 years" |
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current_working_experience = "Senior Java Developer at ABC for 1 year" |
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skilleset= "Java, Spring Boot, Microservices, SQL, AWS" |
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qualification = "Master's in Electronics Science" |
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input_text = f" Generate Cover Letter for Role: {job_title}, \ |
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Preferred Qualifications: {preferred_qualification}, \ |
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Hiring Company: {hiring_company_name}, User Name: {user_name}, \ |
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Past Working Experience: {past_working_experience}, Current Working Experience: {current_working_experience}, \ |
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Skillsets: {skilleset}, Qualifications: {qualification} " |
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# Tokenize and generate predictions |
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input_ids = tokenizer.encode(input_text, return_tensors='pt', max_length=2048, truncation=False, padding=True) |
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input_ids = input_ids.to('cuda') |
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output_ids = model.generate(input_ids) |
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# Decode the output |
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output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True) |
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print("Generated Cover Letter:") |
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print(output_text) |
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``` |
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### Running the model on a CPU |
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```python |
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from transformers import T5Tokenizer, T5ForConditionalGeneration |
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tokenizer = T5Tokenizer.from_pretrained("ShashiVish/t5-base-fine-tune-1024-cover-letter") |
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model = T5ForConditionalGeneration.from_pretrained("ShashiVish/t5-base-fine-tune-1024-cover-letter" , max_length = 512 ) |
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job_title = "Senior Java Developer" |
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preferred_qualification = "3+ years of Java, Spring Boot" |
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hiring_company_name = "Google" |
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user_name = "Emily Evans" |
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past_working_experience= "Java Developer at XYZ for 4 years" |
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current_working_experience = "Senior Java Developer at ABC for 1 year" |
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skilleset= "Java, Spring Boot, Microservices, SQL, AWS" |
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qualification = "Master's in Electronics Science" |
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input_text = f" Generate Cover Letter for Role: {job_title}, \ |
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Preferred Qualifications: {preferred_qualification}, \ |
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Hiring Company: {hiring_company_name}, User Name: {user_name}, \ |
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Past Working Experience: {past_working_experience}, Current Working Experience: {current_working_experience}, \ |
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Skillsets: {skilleset}, Qualifications: {qualification} " |
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# Tokenize and generate predictions |
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input_ids = tokenizer.encode(input_text, return_tensors='pt', max_length=2048, truncation=False, padding=True) |
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output_ids = model.generate(input_ids) |
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# Decode the output |
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output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True) |
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print("Generated Cover Letter:") |
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print(output_text) |
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``` |
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