Chessgpt Chat V1

🚀 Chessgpt-Chat-v1

Chessgpt-Chat-v1 is the sft-tuned model of Chessgpt-Base-v1, aiming to provide high - quality language processing capabilities in the chess domain.

🚀 Quick Start

Chessgpt-Chat-v1 is the sft-tuned model of Chessgpt-Base-v1.

• Base Model: Chessgpt-base-v1
• Chat Version: Chessgpt-chat-v1

Also, we are actively working on the development of the next-generation model, ChessGPT-V2. We welcome any contribution, especially on chess related dataset. For related matters, please contact xidong.feng.20@ucl.ac.uk.

✨ Features

• Model Type: It is a Language Model.
• Language: Supports English.
• License: Under the Apache 2.0 license.
• Model Description: A 2.8B parameter pretrained language model in Chess.

📦 Installation

This requires a GPU with 8GB memory.

import torch
import transformers
from transformers import AutoTokenizer, AutoModelForCausalLM

MIN_TRANSFORMERS_VERSION = '4.25.1'

# check transformers version
assert transformers.__version__ >= MIN_TRANSFORMERS_VERSION, f'Please upgrade transformers to version {MIN_TRANSFORMERS_VERSION} or higher.'

# init
tokenizer = AutoTokenizer.from_pretrained("Waterhorse/chessgpt-chat-v1")
model = AutoModelForCausalLM.from_pretrained("Waterhorse/chessgpt-chat-v1", torch_dtype=torch.float16)
model = model.to('cuda:0')

# infer
# Conversation between two
prompt = "A friendly, helpful chat between some humans.<|endoftext|>Human 0: 1.e4 c5, what is the name of this opening?<|endoftext|>Human 1:"
# Conversation between more than two
#prompt = "A friendly, helpful chat between some humans.<|endoftext|>Human 0: 1.e4 c5, what is the name of this opening?<|endoftext|>Human 1: Sicilian defense.<|endoftext|>Human 2:"

inputs = tokenizer(prompt, return_tensors='pt').to(model.device)
input_length = inputs.input_ids.shape[1]
outputs = model.generate(
    **inputs, max_new_tokens=128, do_sample=True, temperature=0.7, top_p=0.7, top_k=50, return_dict_in_generate=True,
)
token = outputs.sequences[0, input_length:]
output_str = tokenizer.decode(token)
print(output_str)

📚 Documentation

Uses

Excluded uses are described below.

Direct Use

chessgpt-chat-v1 is mainly for research on large language model, especially for those research about policy learning and language modeling.

Out-of-Scope Use

chessgpt-chat-v1 is a language model trained on chess related data and may not perform well for other use cases beyond chess domain.

Bias, Risks, and Limitations

Just as with any language model, chessgpt-chat-v1 carries inherent limitations that necessitate careful consideration. Specifically, it may occasionally generate responses that are irrelevant or incorrect, particularly when tasked with interpreting complex or ambiguous queries. Additionally, given that its training is rooted in online data, the model may inadvertently reflect and perpetuate common online stereotypes and biases.

Evaluation

Please refer to our paper and code for benchmark results.

Citation Information

@article{feng2023chessgpt,
  title={ChessGPT: Bridging Policy Learning and Language Modeling},
  author={Feng, Xidong and Luo, Yicheng and Wang, Ziyan and Tang, Hongrui and Yang, Mengyue and Shao, Kun and Mguni, David and Du, Yali and Wang, Jun},
  journal={arXiv preprint arXiv:2306.09200},
  year={2023}
}

📄 License

This project is licensed under the Apache 2.0 license.