Create app.py

app.py

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+from transformers import (
+    AutoTokenizer,
+    AutoModelForCausalLM,
+    GPTNeoForCausalLM,
+)
+import torch
+import psutil
+tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-2.7B")
+
+model = AutoModelForCausalLM.from_pretrained("NovelAI/genji-python-6B").half().eval().cuda()
+
+import gradio as gr
+
+maxLength=200
+temperature=0.4
+top_k = 50
+top_p = 0.9
+repetition_penalty = 1.13
+repetition_penalty_range = 512
+repetition_penalty_slope = 3.33
+def generator(text):
+    tokens = tokenizer(text, return_tensors="pt").input_ids.cuda()[:, -(2047-maxLength):]
+    out = model.generate(
+        tokens.long(),
+        do_sample=True,
+        min_length=tokens.shape[1] + maxLength,
+        max_length=tokens.shape[1] + maxLength,
+        temperature=temperature,
+        top_k = top_k,
+        top_p = top_p,
+        repetition_penalty = repetition_penalty,
+        repetition_penalty_range = repetition_penalty_range,
+        repetition_penalty_slope = repetition_penalty_slope,
+        use_cache=True,
+        bad_words_ids=None,
+        pad_token_id=tokenizer.eos_token_id,
+    ).long().to("cpu")[0]
+    return tokenizer.decode(out[tokens.shape[1]:])
+
+title = "genji-python-6b"
+description = "demo for Genji-python-6b. To use it, simply add your text, or click one of the examples to load them. Read more at the links below."
+article = "<p style='text-align: center'><a href='https://colab.research.google.com/drive/1PnWpx02IEUkY8jhLKd_NewUGEXahAska'>Colab</a> | <a href='https://huggingface.co/NovelAI/genji-python-6B'>Huggingface Model</a></p>"
+
+gr.Interface(
+    generator, 
+    [gr.inputs.Textbox(label="input text")], 
+    gr.outputs.Textbox(label="Output text"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[
+        ['def print_customer_name']
+    ]).launch(debug=True)