Spaces:
Runtime error
Runtime error
File size: 2,380 Bytes
cc2101c ea4e88a db73536 cc2101c 1ccb976 0f0ea0c 1ccb976 0f0ea0c 44ca16b cc2101c 087e3b8 cc2101c 087e3b8 cc2101c 087e3b8 cc2101c db73536 cc2101c db73536 cc2101c 496d856 b802fa4 cc2101c 478d560 a3a731c a668eef 5af3e9f 478d560 cc2101c 44ca16b db73536 cc2101c 478d560 cc2101c db73536 cc2101c 44ca16b |
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 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 |
import argparse
import itertools
import math
import os
from pathlib import Path
from typing import Optional
import subprocess
import sys
import torch
from spanish_medica_llm import run_training, run_training_process, run_finnetuning_process, generate_response
import gradio as gr
#def greet(name):
# return "Hello " + name + "!!"
#iface = gr.Interface(fn=greet, inputs="text", outputs="text")
#iface.launch()
def generate_model(name):
return f"Welcome to Gradio HF_ACCES_TOKEN, {os.environ.get('HG_FACE_TOKEN')}!"
def generate(prompt):
#from diffusers import StableDiffusionPipeline
#pipe = StableDiffusionPipeline.from_pretrained("./output_model", torch_dtype=torch.float16)
pipe = pipe.to("cuda")
image = pipe(prompt).images[0]
return(image)
def evaluate_model(input):
#from diffusers import StableDiffusionPipeline
#pipe = StableDiffusionPipeline.from_pretrained("./output_model", torch_dtype=torch.float16)
#pipe = pipe.to("cuda")
#image = pipe(prompt).images[0]
output = generate_response(input)
return output
def train_model(*inputs):
if "IS_SHARED_UI" in os.environ:
raise gr.Error("This Space only works in duplicated instances")
run_training_process()
return f"Train Model Sucessful!!!"
def finnetuning_model(*inputs):
if "IS_SHARED_UI" in os.environ:
raise gr.Error("This Space only works in duplicated instances")
run_finnetuning_process()
return f"Finnetuning Model Sucessful!!!"
def stop_model(*input):
return f"Model with Gradio!"
with gr.Blocks() as demo:
gr.Markdown("Start typing below and then click **Run** to see the output.")
with gr.Row():
inp = gr.Textbox(placeholder="What is your name?")
out = gr.Textbox()
btn_response = gr.Button("Generate Response")
btn_response.click(fn=generate_model, inputs=inp, outputs=out)
btn_train = gr.Button("Train Model")
btn_train.click(fn=train_model, inputs=[], outputs=out)
btn_finnetuning = gr.Button("Finnetuning Model")
btn_finnetuning.click(fn=finnetuning_model, inputs=[], outputs=out)
btn_evaluate = gr.Button("Evaluate Model")
btn_evaluate.click(fn=evaluate_model, inputs=inp, outputs=out)
btn_stop = gr.Button("Stop Model")
btn_stop.click(fn=stop_model, inputs=[], outputs=out)
demo.launch() |