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| import gradio as gr | |
| import re | |
| import requests | |
| import json | |
| import os | |
| title = "BLOOM" | |
| description = """Gradio Demo for BLOOM. To use it, simply add your text, or click one of the examples to load them. | |
| Tips: Do NOT talk to BLOOM as an entity, it's not a chatbot but a webpage/blog/article completion model. For the best results: MIMIC a few words of a webpage similar to the content you want to generate. Start a sentence as if YOU were writing a blog, webpage, math post, coding article and BLOOPM will generate a coherent follow-up. | |
| Generation simple selector: | |
| - sampling: imaginative completions (may be not super accurate e.g. math/history) | |
| - greedy: accurate completions (may be more boring or have repetitions) | |
| """ | |
| API_URL = "https://hfbloom.ngrok.io/generate" | |
| HF_API_TOKEN = os.getenv("HF_API_TOKEN") | |
| hf_writer = gr.HuggingFaceDatasetSaver(HF_API_TOKEN, "huggingface/bloom_internal_prompts", organization="huggingface") | |
| examples = [ | |
| ['A "whatpu" is a small, furry animal native to Tanzania. An example of a sentence that uses the word whatpu is: We were traveling in Africa and we saw these very cute whatpus. To do a "farduddle" means to jump up and down really fast. An example of a sentence that uses the word farduddle is:', 32, "Sample"], | |
| ["Pour déguster un ortolan, il faut tout d'abord", 32, "Sample"], | |
| ["Question: If I put cheese into the fridge, will it melt?\nAnswer:", 32, "Sample"], | |
| ["Math exercise - answers:\n34+10=44\n54+20=", 16, "Greedy"], | |
| ["Question: Where does the Greek Goddess Persephone spend half of the year when she is not with her mother?\nAnswer:", 24, "Greedy"], | |
| ["spelling test answers.\nWhat are the letters in « language »?\nAnswer: l-a-n-g-u-a-g-e\nWhat are the letters in « Romanian »?\nAnswer:", 24, "Greedy"], | |
| ] | |
| def query(payload): | |
| print(payload) | |
| response = requests.request("POST", API_URL, json=payload) | |
| print(response) | |
| return json.loads(response.content.decode("utf-8")) | |
| def inference(input_sentence, max_length, sample_or_greedy, seed=42): | |
| if sample_or_greedy == "Sample": | |
| parameters = {"max_new_tokens": max_length, | |
| "top_p": 0.9, | |
| "do_sample": True, | |
| "seed": seed, | |
| "early_stopping": False, | |
| "length_penalty": 0.0, | |
| "eos_token_id": None} | |
| else: | |
| parameters = {"max_new_tokens": max_length, | |
| "do_sample": False, | |
| "seed": seed, | |
| "early_stopping": False, | |
| "length_penalty": 0.0, | |
| "eos_token_id": None} | |
| payload = {"inputs": input_sentence, | |
| "parameters": parameters} | |
| data = query( | |
| payload | |
| ) | |
| print(data) | |
| return data[0]["generated_text"] | |
| gr.Interface( | |
| inference, | |
| [ | |
| gr.inputs.Textbox(label="Input"), | |
| gr.inputs.Slider(1, 64, default=32, step=1, label="Tokens to generate"), | |
| gr.inputs.Radio(["Sample", "Greedy"]), | |
| ], | |
| gr.outputs.Textbox(label="Output"), | |
| examples=examples, | |
| # article=article, | |
| title=title, | |
| description=description, | |
| flagging_callback=hf_writer, | |
| allow_flagging=True, | |
| ).launch() |