File size: 2,422 Bytes
cd6ef49
 
 
 
 
 
 
 
 
90da03b
3a30d63
cd6ef49
 
 
 
 
 
 
dc23734
e5d5fca
 
cd6ef49
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
eb2c646
cd6ef49
2588225
cd6ef49
 
3a30d63
cd6ef49
 
 
 
56285a8
9125212
 
cd6ef49
2b64efc
cd6ef49
9bac66c
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
import gradio as gr
import requests
import os 

##Bloom
API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom"
HF_TOKEN = os.environ["HF_TOKEN"]
headers = {"Authorization": f"Bearer {HF_TOKEN}"}

def text_generate(prompt): 
  print(f"*****Inside TEXT_generate - Prompt is :{prompt}")
  print(f"length of prompt is {len(prompt)}")
    
  json_ = {"inputs": prompt,
            "parameters":
            {
            "top_p": 0.9,
          "temperature": 1.1,
          "max_new_tokens": 250,
          "return_full_text": True,
          "do_sample":True,
          }, 
          "options": 
          {"use_cache": True,
          "wait_for_model": True,
          },}
  response = requests.post(API_URL, headers=headers, json=json_)
  print(f"Response  is : {response}")
  output = response.json()
  print(f"output is : {output}") 
  output_tmp = output[0]['generated_text']
  print(f"output_tmp is: {output_tmp}")
  solution = output_tmp.split("\nQ:")[0]   
  print(f"Final response after splits is: {solution}")
  if '\nOutput:' in solution:
    final_solution = solution.split("\nOutput:")[0] 
    print(f"Response after removing output is: {final_solution}")
  elif '\n\n' in solution:
    final_solution = solution.split("\n\n")[0] 
    print(f"Response after removing new line entries is: {final_solution}")
  else:
    final_solution = solution
  return final_solution 


demo = gr.Blocks()

with demo:
  gr.Markdown("<h1>Bloom Explorer</h1>")
  gr.Markdown(
        """Exploration of the capabilities of the [BigScienceW Bloom](https://twitter.com/BigscienceW) large language model. Currently, due to size-limits on Prompt and Token generation, we are only able to feed very limited-length text as Prompt and are getting very few tokens generated in-turn. This makes it difficult to keep a tab on theme of text generation. This Space is created by [Samim](https://samim.io) for research and fun"""
        )
  with gr.Row():
    input_prompt = gr.Textbox(label="Write text to prompt the model", value="Once upon a time in a land far away", lines=6)
    
  with gr.Row():
    generated_txt = gr.Textbox(lines=3)

  b1 = gr.Button("Generate Text")
  b1.click(text_generate,inputs=[input_prompt], outputs=generated_txt) 
  
  with gr.Row(): 
    gr.Markdown("![visitor badge](https://visitor-badge.glitch.me/badge?page_id=samim-bloom-exploration)")
    
demo.launch(enable_queue=True, debug=True)