Upload 7 files

.gitattributes

@@ -0,0 +1 @@
+anime_rec.pkl filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,12 @@
+---
+title: AnimeRecomendation
+emoji: 🚀
+colorFrom: yellow
+colorTo: blue
+sdk: gradio
+sdk_version: 4.8.0
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

anime_rec.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:333fba6ec54246d3904d5e0a2868a2ccc49d61c2a0b9a8069002e9e5103499fc
+size 14048208

app.py

@@ -0,0 +1,57 @@
+import gradio as gr
+from fastai.learner import load_learner
+import pandas as pd
+import numpy as np
+
+# Modelo
+learn = load_learner('anime_rec.pkl')
+
+# Ids para usar
+id_data = pd.read_csv('dataset.csv')
+id_data = id_data.sort_values('id_user', ascending=True)
+id_list = list(map(str, id_data['id_user'].unique().tolist()))
+
+# Dados originais
+data = pd.read_csv('dataset.csv')
+
+def get_anime_names_by_ids(id_animes):
+    # Filtrar as linhas correspondentes aos id_animes
+    anime_names = data.loc[data['id_anime'].isin(id_animes), ['id_anime', 'name']]
+    # Remover duplicatas
+    anime_names = anime_names.drop_duplicates(subset='id_anime')
+    return anime_names
+
+
+def preds(id_user):
+    id_user = int(id_user)
+
+    itens = pd.Series(learn.dls.classes['id_anime']).unique()
+    itens_series = pd.Series(itens)
+    classifications = data.loc[(data['id_user'] == id_user) & (data['Overall Rating'] > 0), 'id_anime']
+    
+    # Transformar itens em uma Series do Pandas
+    no_classifications = itens_series[~itens_series.isin(classifications)]
+
+    df = pd.DataFrame({'id_user': [id_user] * len(no_classifications), 'id_anime': no_classifications})
+
+    preds, _ = learn.get_preds(dl=learn.dls.test_dl(df))
+
+    df[['prediction']] = preds.numpy()
+
+    top_5 = df.nlargest(5, 'prediction')
+
+    # Obter os nomes dos animes correspondentes aos id_anime
+    result = get_anime_names_by_ids(top_5['id_anime'].astype(int).tolist())
+    result_str = result.apply(lambda x: f"{x['id_anime']}: {x['name']}", axis=1).tolist()
+
+    return '\n'.join(result_str)
+
+iface = gr.Interface(
+    fn=preds, 
+    inputs=gr.Dropdown(choices=id_list), 
+    outputs="text", 
+    title="Recomendador de Animes",
+    description="Esse modelo é capaz de recomendar animes através de um Id de usuário",
+)
+
+iface.launch(share=True)

gitattributes

@@ -0,0 +1,35 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

gitattributes (1)

@@ -0,0 +1,3 @@
+model.pkl filter=lfs diff=lfs merge=lfs -text
+MAL[[:space:]]Anime[[:space:]]Reviews[[:space:]]85k.csv filter=lfs diff=lfs merge=lfs -text
+anime_rec.pkl filter=lfs diff=lfs merge=lfs -text

requirements.txt

@@ -0,0 +1,3 @@
+gradio
+pandas
+fastai