Update README.md

README.md

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 license: cc-by-nc-4.0
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+This model is a generation model trained via [semiparametric token-sequence co-supervision](https://github.com/kaistAI/Semiparametric_Token-Sequence_Co-Supervision) on top of Llama2-7B.
+The embedding model which constructs the nonparametric sequence embedding spaces is in [here](https://huggingface.co/kaist-ai/cosupervision-emb_seq-Llama2_7b).
+The models are trained on information-seeking datasets provided by [self-rag](https://selfrag.github.io/) with co-supervision from next token prediction (NTP) and next sequence prediction (NSP).
+In the inference step, the model generates a response by retrieving relevant sequences.
+See full descriptions in our paper.
+
+### Usage
+Here, we show an easy way to quickly download our model from HuggingFace.
+Make sure to install dependencies listed at requirements.txt. 
+To run our full inference pipeline with embedding model, please use our [code](https://github.com/kaistAI/Semiparametric_Token-Sequence_Co-Supervision).
+
+```
+from transformers import AutoTokenizer, LlamaForCausalLM
+
+model = LlamaForCausalLM.from_pretrained(
+    "kaist-ai/cosupervision-emb_seq-Llama2_7b",
+    load_in_8bit=True if train_config.quantization else None,
+    device_map="auto" if train_config.quantization else None,
+)
+```