Update README.md

About this model.

README.md

@@ -1,3 +1,37 @@
 ---
 license: mit
+language:
+- en
 ---
+
+### What is this?
+A detector based on Facebook's [RoBerta-MUPPET](https://huggingface.co/facebook/muppet-roberta-base) to detect "narrative-style" jokes, stories and anecdotes i.e. they are narrated as a story. See the example in the How to use.
+
+This has not been trained or tested on one-liners, puns or Reddit-style language-manipulation jokes such as knock-knock, Q&A jokes etc.
+
+This model has been developed to detect jokes & anecdotes spoken during speeches or conversations etc.
+
+### Install these first
+You'll need to pip install transformers & maybe sentencepiece
+
+### How to use
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch, time
+device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
+model_name = '/path/to/model'
+max_seq_len = 510
+
+tokenizer = AutoTokenizer.from_pretrained(model_name, model_max_length=max_seq_len)
+model = AutoModelForSequenceClassification.from_pretrained(model_name).to(device)
+
+premise = """A nervous passenger is about to book a flight ticket, and he asks the airlines' ticket seller, "I hope your planes are safe. Do they have a good track record for safety?" The airline agent replies, "Sir, I can guarantee you, we've never had a plane that has crashed more than once." """
+hypothesis = ""
+
+input = tokenizer(premise, hypothesis, truncation=True, return_tensors="pt")
+output = model(input["input_ids"].to(device))  # device = "cuda:0" or "cpu"
+prediction = torch.softmax(output["logits"][0], -1).tolist()
+is_joke = True if prediction[0] < prediction[1] else False
+
+print(is_joke)
+```