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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
import torch
import gradio as gr
# chatgpt-gpt4-prompts-bart-large-cnn-samsum
tokenizer = AutoTokenizer.from_pretrained("Kaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum")
model = AutoModelForSeq2SeqLM.from_pretrained("Kaludi/chatgpt-gpt4-prompts-bart-large-cnn-samsum", from_tf=True)
# zephyr
pipe = pipeline("text-generation", model="HuggingFaceH4/zephyr-7b-alpha", torch_dtype=torch.bfloat16, device_map="auto")
def useZephyr(prompt):
messages = [
{
"role": "system",
"content": "You are a friendly chatbot who always responds in the style of a pirate.",
},
{"role": "user", "content": prompt},
]
# https://huggingface.co/docs/transformers/main/en/chat_templating
prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
print(prompt)
outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
return outputs[0]["generated_text"]
def useZephyr(prompt):
messages = [
{
"role": "system",
"content": "You are a friendly chatbot who always responds in the style of a pirate.",
},
{"role": "user", "content": prompt},
]
# https://huggingface.co/docs/transformers/main/en/chat_templating
outputs = pipe(prompt)
return outputs[0]["generated_text"]
def generatePrompt(prompt, max_new_tokens):
batch = tokenizer(prompt, return_tensors="pt")
generated_ids = model.generate(
batch["input_ids"], max_new_tokens=int(max_new_tokens))
output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
prompt = output[0]
return useZephyr(prompt)
def generate_test(prompt):
batch = tokenizer(prompt, return_tensors="pt")
generated_ids = model.generate(batch["input_ids"], max_new_tokens=150)
output = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
return output[0]
def generate_prompt(prompt, max_new_tokens):
return generatePrompt(prompt, max_new_tokens)
#
# Interface
input_prompt = gr.Textbox(label="Prompt", value="photographer")
input_maxtokens = gr.Textbox(label="Max tokens", value="150")
output_component = gr.Textbox(label="Output")
examples = [["photographer"], ["developer"], ["teacher"], [
"human resources staff"], ["recipe for ham croquettes"]]
description = ""
PerfectGPT = gr.Interface(useZephyr, inputs=[input_prompt, input_maxtokens], outputs=output_component,
examples=examples, title="🗿 PerfectGPT v1 🗿", description=description)
PerfectGPT.launch() |