rohitkumarai/my_tinybert_encoder

1---2tags:3- transformers4- text-classification5- text-embedding6- tinybert7license: apache-2.08library_name: transformers9widget:10  - text: "Encode this text using TinyBERT"11---12 13# 🚀 TinyBERT Encoder Model14 15This is a fine-tuned **TinyBERT Encoder** model, optimized for lightweight NLP tasks.16 17## 🔹 Use This Model18 19To use this model with **transformers**, simply run:20 21```python22from transformers import AutoModel, AutoTokenizer23 24model_name = "hjsgfd/my_tinybert_encoder"  # Replace with your actual repo name25tokenizer = AutoTokenizer.from_pretrained(model_name)26model = AutoModel.from_pretrained(model_name)27 28# Encode text29text = "TinyBERT is small but powerful."30inputs = tokenizer(text, return_tensors="pt")31outputs = model(**inputs)32 33print(outputs.last_hidden_state)  # Encoded text representation34 35 36from sentence_transformers import SentenceTransformer37 38model = SentenceTransformer("hjsgfd/my_tinybert_encoder")39embeddings = model.encode("This is an example sentence.")40print(embeddings)41---42 43 44# TinyBERT Encoder Model45 46This is a fine-tuned **TinyBERT Encoder** model optimized for lightweight NLP tasks.47 48## 🔹 How to Use49 50```python51from transformers import AutoModel, AutoTokenizer52 53model_name = " hjsgfd/my_tinybert_encoder"54tokenizer = AutoTokenizer.from_pretrained(model_name)55model = AutoModel.from_pretrained(model_name)56 57# Encode text58text = "TinyBERT is small but powerful."59inputs = tokenizer(text, return_tensors="pt")60outputs = model(**inputs)61 62print(outputs.last_hidden_state)  # Encoded text representation63