Upload app.py

app.py

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+# -*- coding: utf-8 -*-
+"""Motivation-Letter-Generator
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1ZjAxQWoA9ECi-WgAMVm0HyonnrFFMlHG
+"""
+
+! pip install transformers
+! pip install gradio
+
+from transformers import AutoModelForCausalLM, AutoTokenizer, set_seed, pipeline
+import gradio as gr
+
+import torch
+torch.set_default_tensor_type(torch.cuda.FloatTensor)
+
+### need more GPU power to call better models !!!!!!
+
+# from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+# tokenizer = AutoTokenizer.from_pretrained("bigscience/T0pp")
+# model = AutoModelForSeq2SeqLM.from_pretrained("bigscience/T0pp") # 11B param
+
+model = AutoModelForCausalLM.from_pretrained('EleutherAI/gpt-neo-1.3B', use_cache=True)
+tokenizer = AutoTokenizer.from_pretrained('EleutherAI/gpt-neo-1.3B')
+
+set_seed(424242)
+
+def generate(Name, Employer, Position, Organization, Hard_skills, Soft_skills, max_length=500, top_k=1, temperature=0.9, repetition_penalty = 2.0):
+  prompt = f'im {Name} and i want to write a motivation letter to {Employer} about the position {Position} at {Organization} mentioning the hard skills {Hard_skills} and soft skills {Soft_skills} you have acquired'
+  input_ids = tokenizer(prompt, return_tensors="pt").to(0)
+  sample = model.generate(**input_ids, max_length=max_length,  top_k=top_k, temperature=temperature, repetition_penalty = repetition_penalty)
+  return tokenizer.decode(sample[0], truncate_before_pattern=[r"\n\n^#", "^'''", "\n\n\n"])
+
+title = "Motivation Letter Generator w/ GPT-Neo-1.3B"
+article = "Colab is not really offering GPUs to load the big guns like 176B BLOOM so this is a toy demo, But if you have enough resources feel free to contact me and i'll send you the notebook, my contact: ali.elfilali00@gmail.com"
+
+gr.Interface(
+    fn=generate,
+    inputs=["text", "text", "text", "text", "text", "text"],
+    outputs="text",
+    title=title,
+    article=article).launch()
+
+
+