Update README.md

README.md

@@ -1,3 +1,82 @@
 ---
+language:
+- hu
+- en
+- zh
+tags:
+- text-generation
 license: cc-by-nc-4.0
+widget:
+- text: Elmesélek egy történetet a nyelvtechnológiáról.
 ---
+
+# PULI GPTrio (6.7 billion parameter)
+
+For further details, see [our demo site](https://juniper.nytud.hu/demo/gptrio).
+
+  - Hungarian-English-Chinese trilingual GPT-NeoX model (6.7 billion parameter)
+  - Trained with EleutherAI's GPT-NeoX [github](https://github.com/EleutherAI/gpt-neox)
+  - Checkpoint: 410 000 steps
+
+## Dataset
+
+- Hungarian: 41 508 933 801 words (314 GB)
+- English: 61 906 491 82 words (391 GB)
+- Github: 6 018 366 documents (33 GB)
+- Chinese: 98 693 705 456 Chinese character (340 GB)
+  - (12 072 234 774 non Chinese token)
+
+## Limitations
+
+- max_seq_length = 2048
+- float16
+
+
+## Citation
+If you use this model, please cite the following paper:
+
+```
+@inproceedings {yang-puli-gptrio,
+    title = {Mono- and multilingual GPT-3 models for Hungarian},
+	booktitle = {Text, Speech, and Dialogue - 26th International Conference, {TSD} 2023, Proceedings},
+	year = {2023},
+	publisher = {Springer},
+    series = {Lecture Notes in Computer Science},
+	address = {Plzeň, Czech Republic},
+	author = {Yang, Zijian Győző and Laki, László János and Váradi, Tamás and Prószéky, Gábor},
+	pages = {Accepted}
+}
+```
+
+## Usage
+
+```python
+from transformers import GPTNeoXForCausalLM, GPTNeoXTokenizerFast
+
+model = GPTNeoXForCausalLM.from_pretrained("NYTK/PULI-GPTrio")
+tokenizer = GPTNeoXTokenizerFast.from_pretrained("NYTK/PULI-GPTrio")
+prompt = "Elmesélek egy történetet a nyelvtechnológiáról."
+input_ids = tokenizer(prompt, return_tensors="pt").input_ids
+
+gen_tokens = model.generate(
+    input_ids,
+    do_sample=True,
+    temperature=0.9,
+    max_length=100,
+)
+
+gen_text = tokenizer.batch_decode(gen_tokens)[0]
+print(gen_text)
+```
+## Usage with pipeline
+
+```python
+from transformers import pipeline, GPTNeoXForCausalLM, GPTNeoXTokenizerFast
+
+model = GPTNeoXForCausalLM.from_pretrained("NYTK/PULI-GPTrio")
+tokenizer = GPTNeoXTokenizerFast.from_pretrained("NYTK/PULI-GPTrio")
+prompt = "Elmesélek egy történetet a nyelvtechnológiáról."
+generator = pipeline(task="text-generation", model=model, tokenizer=tokenizer)
+
+print(generator(prompt)[0]["generated_text"])
+```