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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}
-}
-```