Update README.md

README.md

@@ -1,3 +1,59 @@
 ---
 license: apache-2.0
+library_name: keras
 ---
+# BiLSTM Sentiment Classifier (Teeny-Tiny Castle)
+
+This model is part of a tutorial tied to the [Teeny-Tiny Castle](https://github.com/Nkluge-correa/TeenyTinyCastle), an open-source repository containing educational tools for AI Ethics and Safety research. 
+
+## How to Use
+
+```python
+from huggingface_hub import hf_hub_download
+
+# Download the model
+hf_hub_download(repo_id="AiresPucrs/BiLSTM-sentiment-classifier",
+                filename="BiLSTM-sentiment-classifier.h5",
+                local_dir="./",
+                repo_type="model"
+ )
+
+# Download the tokenizer file
+hf_hub_download(repo_id="AiresPucrs/BiLSTM-sentiment-classifier",
+                filename="tokenizer-BiLSTM-sentiment-classifier.json",
+                local_dir="./",
+                repo_type="model"
+ )
+
+import json
+import torch
+import numpy as np
+import pandas as pd
+import tensorflow as tf
+
+model = tf.keras.models.load_model('./BiLSTM-sentiment-classifier.h5')
+
+with open('./tokenizer-BiLSTM-sentiment-classifier.json') as fp:
+ data = json.load(fp)
+ tokenizer = tf.keras.preprocessing.text.tokenizer_from_json(data)
+ fp.close()
+
+strings = [
+    'this explanation is really bad',
+    'i did not like this tutorial 2/10',
+    'this tutorial is garbage i wont my money back',
+    'is nice to see philosophers doing machine learning',
+    'this is a great and wonderful example of nlp',
+    'this tutorial is great one of the best tutorials ever made'
+]
+
+preds = model.predict(
+ tf.keras.preprocessing.sequence.pad_sequences(
+ tokenizer.texts_to_sequences(strings),
+        maxlen=250,
+        truncating='post'
+ ), verbose=0)
+
+for i, string in enumerate(strings):
+    print(f'Review: "{string}"\n(Negative 😊 {round((preds[i][0]) * 100)}% | Positive 😔 {round(preds[i][1] * 100)}%)\n')
+```