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README.md

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+---
+license: mit
+pipeline_tag: text-generation
+tags:
+- ocean
+- text-generation-inference
+- oceangpt
+language:
+- en
+datasets:
+- zjunlp/OceanBench
+---
+
+## 💡 Model description
+This repo contains a large language model (OceanGPT) for ocean  science tasks trained with [KnowLM](https://github.com/zjunlp/KnowLM). 
+It should be noted that the OceanGPT is constantly being updated, so the current model is not the final version.
+
+OceanGPT-7B-v0.2 is based on Qwen2-7B and trained on a bilingual dataset in Chinese and English.
+## 🔍 Intended uses
+You can download the model to generate responses or contact the [email](bizhen_zju@zju.edu.cn) for the online test demo.
+
+## 🛠️ How to use OceanGPT
+We wil provide several examples soon and you can modify the input according to your needs.
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+device = "cuda" # the device to load the model onto
+
+model = AutoModelForCausalLM.from_pretrained(
+    "zjunlp/OceanGPT-7B-v0.2",
+    torch_dtype=torch.bfloat16,
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained("zjunlp/OceanGPT-7B-v0.2")
+
+prompt = "Which is the largest ocean in the world?"
+messages = [
+    {"role": "system", "content": "You are a helpful assistant."},
+    {"role": "user", "content": prompt}
+]
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+model_inputs = tokenizer([text], return_tensors="pt").to(device)
+
+generated_ids = model.generate(
+    model_inputs.input_ids,
+    max_new_tokens=512
+)
+generated_ids = [
+    output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+]
+
+response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+```
+
+## 🛠️ How to evaluate your model in OceanBench
+
+We wil provide several examples soon and you can modify the input according to your needs.
+
+*Note: We are conducting the final checks on OceanBench and will be uploading it to Hugging Face soon. 
+
+```python
+>>> from datasets import load_dataset
+
+>>> dataset = load_dataset("zjunlp/OceanBench")
+```
+
+## 📚 How to cite
+
+```bibtex
+@article{bi2023oceangpt,
+  title={OceanGPT: A Large Language Model for Ocean Science Tasks},
+  author={Bi, Zhen and Zhang, Ningyu and Xue, Yida and Ou, Yixin and Ji, Daxiong and Zheng, Guozhou and Chen, Huajun},
+  journal={arXiv preprint arXiv:2310.02031},
+  year={2023}
+}
+```