cpm-ant-10b
About this model
Usage
pip install transformers
from transformers import CpmAntTokenizer, CpmAntForCausalLM
texts = "今天天气不错，"
model = CpmAntForCausalLM.from_pretrained("openbmb/cpm-ant-10b")
tokenizer = CpmAntTokenizer.from_pretrained("openbmb/cpm-ant-10b")
input_ids = tokenizer(texts, return_tensors="pt")
outputs = model.generate(**input_ids)
output_texts = tokenizer.batch_decode(outputs)
print(output_texts)
Technical Specs
- Parameters: 10.0B
- Architecture: Transformer
- Context Window: 2,048 tokens
- Input Modalities: text
Hardware Requirements
- VRAM: 20.0 GB
- Compute: Single NVIDIA RTX 3090 24GB for standard FP16 inference; BMInf enables 10B inference on GTX 1060 6GB with 16GB system RAM
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