samz/minimind-pretrain

MiniMind Pretrained Model

Chinese language model trained on pretrain dataset.

Model Details

• Architecture: Transformer
• Parameters: 26.878M
• Dimensions: 512
• Layers: 8
• Attention Heads: 8
• Vocabulary Size: 32000
• Max Sequence Length: 1024

Training Data

• Pretrained on Chinese text corpus
• Dataset size: 4.33GB

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("samz/minimind-pretrain")
tokenizer = AutoTokenizer.from_pretrained("samz/minimind-pretrain")

text = "今天天气真不错"
inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_length=50)
result = tokenizer.decode(outputs[0])
print(result)