Update README.md

README.md

@@ -6,4 +6,55 @@ language:
 metrics:
 - bertscore
 pipeline_tag: text2text-generation
----
+---
+
+# EmojiLM
+
+This is a [BART](facebook/bart-large) model pre-trained on the [Test2Emoji](https://huggingface.co/datasets/KomeijiForce/Text2Emoji) dataset to translate setences into series of emojis.
+
+For instance, "I love pizza" will be translated into "🍕😍".
+
+An example implementation for translation:
+
+```python
+from transformers import BartTokenizer, BartForConditionalGeneration
+
+def translate(sentence, **argv):
+    inputs = tokenizer(sentence, return_tensors="pt")
+    generated_ids = generator.generate(inputs["input_ids"], **argv)
+    decoded = tokenizer.decode(generated_ids[0], skip_special_tokens=True).replace(" ", "")
+    return decoded
+
+path = "KomeijiForce/bart-large-emojilm"
+tokenizer = BartTokenizer.from_pretrained(path)
+generator = BartForConditionalGeneration.from_pretrained(path)
+
+sentence = "I love the weather in Alaska!"
+decoded = translate(sentence, num_beams=4, do_sample=True, max_length=100)
+print(decoded)
+```
+
+You will probably get some output like "❄️🏔️😍".
+
+If you find this model & dataset resource useful, please consider cite our paper:
+
+```
+@article{DBLP:journals/corr/abs-2311-01751,
+  author       = {Letian Peng and
+                  Zilong Wang and
+                  Hang Liu and
+                  Zihan Wang and
+                  Jingbo Shang},
+  title        = {EmojiLM: Modeling the New Emoji Language},
+  journal      = {CoRR},
+  volume       = {abs/2311.01751},
+  year         = {2023},
+  url          = {https://doi.org/10.48550/arXiv.2311.01751},
+  doi          = {10.48550/ARXIV.2311.01751},
+  eprinttype    = {arXiv},
+  eprint       = {2311.01751},
+  timestamp    = {Tue, 07 Nov 2023 18:17:14 +0100},
+  biburl       = {https://dblp.org/rec/journals/corr/abs-2311-01751.bib},
+  bibsource    = {dblp computer science bibliography, https://dblp.org}
+}
+```