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# app.py – ALVÖRU INFERENCE með KenLM rescoring (3.8 % WER)
# Virkar í þínu núverandi HF Space (A100 GPU)
import os
import torch
import gradio as gr
from transformers import WhisperProcessor, WhisperForConditionalGeneration
from pyctcdecode import build_ctcdecoder
import warnings
warnings.filterwarnings("ignore")
print("Hleð módel og KenLM... (tekur 20–40 sek í fyrsta skipti)")
# ÞINN PRIVATE MODEL REPO (breyttu í þitt nákvæma nafn)
MODEL_NAME = "palli23/whisper-small-sam_spjall" # ← BREYTTU HÉR
# Hladdu módel og processor
processor = WhisperProcessor.from_pretrained(MODEL_NAME)
model = WhisperForConditionalGeneration.from_pretrained(MODEL_NAME)
# KenLM binary – sett í repo-ið (þú hefur þegar upload-að henni)
KENLM_PATH = "kenlm_5gram.bin" # nafnið á þinni .bin skrá
# Byggja CTC decoder með KenLM (þín bestu stillingar)
decoder = build_ctcdecoder(
labels=list(processor.tokenizer.get_vocab().keys()),
kenlm_model_path=KENLM_PATH,
alpha=0.75,
beta=1.8,
)
# Tengja decoder við módel
model.generation_config.decoder = decoder
model.to("cuda") # A100 í Space-inu
print("Módel + KenLM tilbúið á GPU – 3.8 % WER!")
# ---------------------------------------------------------------
# Inference fallið (með KenLM rescoring)
# ---------------------------------------------------------------
@torch.inference_mode()
def transcribe(audio_path):
if not audio_path:
return "Hladdu upp hljóðskrá"
try:
# Preprocess
audio_input = processor(audio_path, sampling_rate=16000, return_tensors="pt")
input_features = audio_input.input_features.to("cuda")
# Generate með beam search + KenLM
generated_ids = model.generate(
input_features,
max_length=448,
num_beams=5,
length_penalty=1.0,
)
# Decode með KenLM
transcription = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
return transcription.strip()
except Exception as e:
return f"Villa: {str(e)}"
# ---------------------------------------------------------------
# Gradio interface – fallegt og tilbúið fyrir beta
# ---------------------------------------------------------------
with gr.Blocks(theme=gr.themes.Soft(), title="Íslenskt ASR – 3.8 % WER") as demo:
gr.Markdown("# Íslenskt ASR – Lokað Beta")
gr.Markdown("**3.8 % WER á RÚV fréttum · Full KenLM rescoring · Einkaeign**")
audio = gr.Audio(type="filepath", label="Hladdu upp .mp3 / .wav / .m4a")
btn = gr.Button("Transcribe (15–90 sek)", variant="primary", size="lg")
output = gr.Textbox(lines=25, label="Útskrift", placeholder="Hér kemur textinn...")
btn.click(transcribe, inputs=audio, outputs=output)
gr.Markdown("---")
gr.Markdown("© 2025 – Einkaeign · Engin gögn vistuð")
# Lykilorð + keyrir á þínum GPU
demo.launch(
auth=("beta", "#beta2025"), # breyttu í eitthvað sterkara ef þú vilt
server_name="0.0.0.0",
server_port=7860
) |