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import gradio as gr
from gradio_huggingfacehub_search import HuggingfaceHubSearch
import requests
processed_inputs = {}
def process_inputs(model_id, q_method, email, oauth_token: gr.OAuthToken | None, profile: gr.OAuthProfile | None):
if oauth_token.token is None or profile.username is None:
return "You must be logged in to use this service."
if not model_id or not q_method or not email:
return "All fields are required!"
input_hash = hash((model_id, q_method, oauth_token.token, profile.username))
if input_hash in processed_inputs and processed_inputs[input_hash] == 200:
return "This request has already been submitted successfully. Please do not submit the same request multiple times."
url = "https://sdk.nexa4ai.com/convert--to--gguf"
params = {
"repository_url": f"https://huggingface.co/{model_id}",
"username": profile.username,
"access_token": oauth_token.token,
"email": email,
"quantization_option": q_method,
}
response = requests.post(url, params=params)
if response.status_code == 200:
processed_inputs[input_hash] = 200
return "Your request has been submitted successfully. We will notify you by email once processing is complete. There is no need to submit the same request multiple times."
else:
processed_inputs[input_hash] = response.status_code
return f"Failed to submit request: {response.text}"
iface = gr.Interface(
fn=process_inputs,
inputs=[
HuggingfaceHubSearch(
label="Hub Model ID",
placeholder="Search for model id on Huggingface",
search_type="model",
),
gr.Dropdown(
["Q2_K", "Q3_K_S", "Q3_K_M", "Q3_K_L", "Q4_0", "Q4_K_S", "Q4_K_M", "Q5_0", "Q5_K_S", "Q5_K_M", "Q6_K", "Q8_0"],
label="Quantization Method",
info="GGML quantisation type",
value="Q4_K_M",
filterable=False
),
gr.Textbox(label="Email", placeholder="Enter your email here")
],
outputs=gr.Markdown(label="output", value="Please enter the model URL, select a quantization method, and provide your email address.",),
title="Create your own GGUF Quants, blazingly fast ⚡!",
allow_flagging="never"
)
theme = gr.themes.Base()
with gr.Blocks(theme=theme) as demo:
gr.Markdown("You must be logged in to use this service.")
gr.LoginButton(min_width=250)
iface.render()
demo.launch(share=True)
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