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| import json | |
| import math | |
| import random | |
| import os | |
| import streamlit as st | |
| import lyricsgenius | |
| import transformers | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| st.set_page_config(page_title="HuggingArtists") | |
| st.title("HuggingArtists") | |
| st.sidebar.markdown( | |
| """ | |
| <style> | |
| .aligncenter { | |
| text-align: center; | |
| } | |
| </style> | |
| <p class="aligncenter"> | |
| <img src="https://raw.githubusercontent.com/AlekseyKorshuk/huggingartists/master/img/logo.jpg" width="420" /> | |
| </p> | |
| """, | |
| unsafe_allow_html=True, | |
| ) | |
| st.sidebar.markdown( | |
| """ | |
| <style> | |
| .aligncenter { | |
| text-align: center; | |
| } | |
| </style> | |
| <p style='text-align: center'> | |
| <a href="https://github.com/AlekseyKorshuk/huggingartists" target="_blank">GitHub</a> | <a href="https://wandb.ai/huggingartists/huggingartists/reportlist" target="_blank">Project Report</a> | |
| </p> | |
| <p class="aligncenter"> | |
| <a href="https://github.com/AlekseyKorshuk/huggingartists" target="_blank"> | |
| <img src="https://img.shields.io/github/stars/AlekseyKorshuk/huggingartists?style=social"/> | |
| </a> | |
| </p> | |
| <p class="aligncenter"> | |
| <a href="https://t.me/joinchat/_CQ04KjcJ-4yZTky" target="_blank"> | |
| <img src="https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram"/> | |
| </a> | |
| </p> | |
| <p class="aligncenter"> | |
| <a href="https://colab.research.google.com/github/AlekseyKorshuk/huggingartists/blob/master/huggingartists-demo.ipynb" target="_blank"> | |
| <img src="https://colab.research.google.com/assets/colab-badge.svg"/> | |
| </a> | |
| </p> | |
| """, | |
| unsafe_allow_html=True, | |
| ) | |
| st.sidebar.header("Generation settings:") | |
| num_sequences = st.sidebar.number_input( | |
| "Number of sequences to generate", | |
| min_value=1, | |
| value=5, | |
| help="The amount of generated texts", | |
| ) | |
| min_length = st.sidebar.number_input( | |
| "Minimum length of the sequence", | |
| min_value=1, | |
| value=100, | |
| help="The minimum length of the sequence to be generated", | |
| ) | |
| max_length= st.sidebar.number_input( | |
| "Maximum length of the sequence", | |
| min_value=1, | |
| value=160, | |
| help="The maximum length of the sequence to be generated", | |
| ) | |
| temperature = st.sidebar.slider( | |
| "Temperature", | |
| min_value=0.0, | |
| max_value=3.0, | |
| step=0.01, | |
| value=1.0, | |
| help="The value used to module the next token probabilities", | |
| ) | |
| top_p = st.sidebar.slider( | |
| "Top-P", | |
| min_value=0.0, | |
| max_value=1.0, | |
| step=0.01, | |
| value=0.95, | |
| help="If set to float < 1, only the most probable tokens with probabilities that add up to top_p or higher are kept for generation.", | |
| ) | |
| top_k= st.sidebar.number_input( | |
| "Top-K", | |
| min_value=0, | |
| value=50, | |
| step=1, | |
| help="The number of highest probability vocabulary tokens to keep for top-k-filtering.", | |
| ) | |
| caption = ( | |
| "In [HuggingArtists](https://github.com/AlekseyKorshuk/huggingartist), we can generate lyrics by a specific artist. This was made by fine-tuning a pre-trained [HuggingFace Transformer](https://huggingface.co) on parsed datasets from [Genius](https://genius.com)." | |
| ) | |
| st.markdown("[HuggingArtists](https://github.com/AlekseyKorshuk/huggingartist) - Train a model to generate lyrics 🎵") | |
| st.markdown(caption) | |
| st.subheader("Settings:") | |
| artist_name = st.text_input("Artist name:", "Eminem") | |
| start = st.text_input("Beginning of the song:", "But for me to rap like a computer") | |
| TOKEN = "q_JK_BFy9OMiG7fGTzL-nUto9JDv3iXI24aYRrQnkOvjSCSbY4BuFIindweRsr5I" | |
| genius = lyricsgenius.Genius(TOKEN) | |
| model_html = """ | |
| <div class="inline-flex flex-col" style="line-height: 1.5;"> | |
| <div class="flex"> | |
| <div | |
| \t\t\tstyle="display:DISPLAY_1; margin-left: auto; margin-right: auto; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('USER_PROFILE')"> | |
| </div> | |
| </div> | |
| <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 HuggingArtists Model 🤖</div> | |
| <div style="text-align: center; font-size: 16px; font-weight: 800">USER_NAME</div> | |
| <a href="https://genius.com/artists/USER_HANDLE"> | |
| \t<div style="text-align: center; font-size: 14px;">@USER_HANDLE</div> | |
| </a> | |
| </div> | |
| """ | |
| def post_process(output_sequences): | |
| predictions = [] | |
| generated_sequences = [] | |
| max_repeat = 2 | |
| # decode prediction | |
| for generated_sequence_idx, generated_sequence in enumerate(output_sequences): | |
| generated_sequence = generated_sequence.tolist() | |
| text = tokenizer.decode(generated_sequence, clean_up_tokenization_spaces=True, skip_special_tokens=True) | |
| generated_sequences.append(text.strip()) | |
| for i, g in enumerate(generated_sequences): | |
| res = str(g).replace('\n\n\n', '\n').replace('\n\n', '\n') | |
| lines = res.split('\n') | |
| # print(lines) | |
| # i = max_repeat | |
| # while i != len(lines): | |
| # remove_count = 0 | |
| # for index in range(0, max_repeat): | |
| # # print(i - index - 1, i - index) | |
| # if lines[i - index - 1] == lines[i - index]: | |
| # remove_count += 1 | |
| # if remove_count == max_repeat: | |
| # lines.pop(i) | |
| # i -= 1 | |
| # else: | |
| # i += 1 | |
| predictions.append('\n'.join(lines)) | |
| return predictions | |
| if st.button("Run"): | |
| model_name = None | |
| with st.spinner(text=f"Searching for {artist_name } in Genius..."): | |
| artist = genius.search_artist(artist_name, max_songs=0, get_full_info=False) | |
| if artist is not None: | |
| artist_dict = genius.artist(artist.id)['artist'] | |
| artist_url = str(artist_dict['url']) | |
| model_name = artist_url[artist_url.rfind('/') + 1:].lower() | |
| st.markdown(model_html.replace("USER_PROFILE",artist.image_url).replace("USER_NAME",artist.name).replace("USER_HANDLE",model_name), unsafe_allow_html=True) | |
| else: | |
| st.markdown(f"Could not find {artist_name}! Be sure that he/she exists in [Genius](https://genius.com/).") | |
| if model_name is not None: | |
| with st.spinner(text=f"Downloading the model of {artist_name }..."): | |
| model = None | |
| tokenizer = None | |
| try: | |
| tokenizer = AutoTokenizer.from_pretrained(f"huggingartists/{model_name}") | |
| model = AutoModelForCausalLM.from_pretrained(f"huggingartists/{model_name}") | |
| except Exception as ex: | |
| # st.markdown(ex) | |
| st.markdown(f"Model for this artist does not exist yet. Create it in just 5 min with [Colab Notebook](https://colab.research.google.com/github/AlekseyKorshuk/huggingartists/blob/master/huggingartists-demo.ipynb):") | |
| st.markdown( | |
| """ | |
| <style> | |
| .aligncenter { | |
| text-align: center; | |
| } | |
| </style> | |
| <p class="aligncenter"> | |
| <a href="https://colab.research.google.com/github/AlekseyKorshuk/huggingartists/blob/master/huggingartists-demo.ipynb" target="_blank"> | |
| <img src="https://colab.research.google.com/assets/colab-badge.svg"/> | |
| </a> | |
| </p> | |
| """, | |
| unsafe_allow_html=True, | |
| ) | |
| if model is not None: | |
| with st.spinner(text=f"Generating lyrics..."): | |
| encoded_prompt = tokenizer(start, add_special_tokens=False, return_tensors="pt").input_ids | |
| encoded_prompt = encoded_prompt.to(model.device) | |
| # prediction | |
| output_sequences = model.generate( | |
| input_ids=encoded_prompt, | |
| max_length=max_length, | |
| min_length=min_length, | |
| temperature=float(temperature), | |
| top_p=float(top_p), | |
| top_k=int(top_k), | |
| do_sample=True, | |
| repetition_penalty=1.0, | |
| num_return_sequences=num_sequences | |
| ) | |
| # Post-processing | |
| predictions = post_process(output_sequences) | |
| st.subheader("Results") | |
| for prediction in predictions: | |
| st.text(prediction) | |
| st.subheader("Please star this repository and join my Telegram Channel:") | |
| st.markdown( | |
| """ | |
| <style> | |
| .aligncenter { | |
| text-align: center; | |
| } | |
| </style> | |
| <p class="aligncenter"> | |
| <a href="https://github.com/AlekseyKorshuk/huggingartists" target="_blank"> | |
| <img src="https://img.shields.io/github/stars/AlekseyKorshuk/huggingartists?style=social"/> | |
| </a> | |
| </p> | |
| <p class="aligncenter"> | |
| <a href="https://t.me/joinchat/_CQ04KjcJ-4yZTky" target="_blank"> | |
| <img src="https://img.shields.io/badge/dynamic/json?color=blue&label=Telegram%20Channel&query=%24.result&url=https%3A%2F%2Fapi.telegram.org%2Fbot1929545866%3AAAFGhV-KKnegEcLiyYJxsc4zV6C-bdPEBtQ%2FgetChatMemberCount%3Fchat_id%3D-1001253621662&style=social&logo=telegram"/> | |
| </a> | |
| </p> | |
| """, | |
| unsafe_allow_html=True, | |
| ) |