Views
No views yet
1
2from transformers import T5Tokenizer, T5ForConditionalGeneration
3
4tokenizer = T5Tokenizer.from_pretrained("ShashiVish/t5-base-fine-tune-1024-cover-letter")
5model = T5ForConditionalGeneration.from_pretrained("ShashiVish/t5-base-fine-tune-1024-cover-letter" , max_length = 512 , device_map="auto")
6
7job_title = "Senior Java Developer"
8preferred_qualification = "3+ years of Java, Spring Boot"
9hiring_company_name = "Google"
10user_name = "Emily Evans"
11past_working_experience= "Java Developer at XYZ for 4 years"
12current_working_experience = "Senior Java Developer at ABC for 1 year"
13skilleset= "Java, Spring Boot, Microservices, SQL, AWS"
14qualification = "Master's in Electronics Science"
15
16
17input_text = f" Generate Cover Letter for Role: {job_title}, \
18 Preferred Qualifications: {preferred_qualification}, \
19 Hiring Company: {hiring_company_name}, User Name: {user_name}, \
20 Past Working Experience: {past_working_experience}, Current Working Experience: {current_working_experience}, \
21 Skillsets: {skilleset}, Qualifications: {qualification} "
22
23# Tokenize and generate predictions
24input_ids = tokenizer.encode(input_text, return_tensors='pt', max_length=2048, truncation=False, padding=True)
25input_ids = input_ids.to('cuda')
26output_ids = model.generate(input_ids)
27
28# Decode the output
29output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
30
31print("Generated Cover Letter:")
32print(output_text)
331
2from transformers import T5Tokenizer, T5ForConditionalGeneration
3
4tokenizer = T5Tokenizer.from_pretrained("ShashiVish/t5-base-fine-tune-1024-cover-letter")
5model = T5ForConditionalGeneration.from_pretrained("ShashiVish/t5-base-fine-tune-1024-cover-letter" , max_length = 512 )
6
7job_title = "Senior Java Developer"
8preferred_qualification = "3+ years of Java, Spring Boot"
9hiring_company_name = "Google"
10user_name = "Emily Evans"
11past_working_experience= "Java Developer at XYZ for 4 years"
12current_working_experience = "Senior Java Developer at ABC for 1 year"
13skilleset= "Java, Spring Boot, Microservices, SQL, AWS"
14qualification = "Master's in Electronics Science"
15
16
17input_text = f" Generate Cover Letter for Role: {job_title}, \
18 Preferred Qualifications: {preferred_qualification}, \
19 Hiring Company: {hiring_company_name}, User Name: {user_name}, \
20 Past Working Experience: {past_working_experience}, Current Working Experience: {current_working_experience}, \
21 Skillsets: {skilleset}, Qualifications: {qualification} "
22
23# Tokenize and generate predictions
24input_ids = tokenizer.encode(input_text, return_tensors='pt', max_length=2048, truncation=False, padding=True)
25output_ids = model.generate(input_ids)
26
27# Decode the output
28output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
29
30print("Generated Cover Letter:")
31print(output_text)
32