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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) |