created README

README.md

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+This is a masked language model that was trained on IMDB dataset using a finetuned DistilBERT model. 
+
+# Rest API Code for Testing the Masked Language Model
+
+Inference API python code for testing the masked language model.
+``` python
+import requests
+
+API_URL = "https://api-inference.huggingface.co/models/ayoolaolafenwa/Masked-Language-Model"
+headers = {"Authorization": "Bearer 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"}
+
+def query(payload):
+	response = requests.post(API_URL, headers=headers, json=payload)
+	return response.json()
+	
+output = query({
+	"inputs": "Washington DC is the [MASK] of USA.",
+})
+print(output[0]["sequence"])
+```
+
+Output
+```
+washington dc is the capital of usa.
+```
+It produces the correct output, *washington dc is the capital of usa.*
+
+## Load the Masked Language Model with Transformers
+You can easily load the Language model with transformers using this code.
+``` python
+from transformers import AutoTokenizer, AutoModelForMaskedLM
+import torch
+
+tokenizer = AutoTokenizer.from_pretrained("ayoolaolafenwa/Masked-Language-Model")
+
+model = AutoModelForMaskedLM.from_pretrained("ayoolaolafenwa/Masked-Language-Model") 
+
+inputs = tokenizer("The internet [MASK] amazing.", return_tensors="pt")
+
+
+with torch.no_grad():
+    logits = model(**inputs).logits
+
+# retrieve index of [MASK]
+mask_token_index = (inputs.input_ids == tokenizer.mask_token_id)[0].nonzero(as_tuple=True)[0]
+
+predicted_token_id = logits[0, mask_token_index].argmax(axis=-1)
+output = tokenizer.decode(predicted_token_id)
+print(output)
+```
+Output
+```
+is 
+```
+
+It prints out the predicted masked word *is*.