glm-edge-v-2b / README_zh.md
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# GLM-Edge-V-2B
## 使用 transformers 库进行推理
### 安装
请安装源代码的transformers库。
```shell
pip install git+https://github.com/huggingface/transformers.git
```
### 推理
```python
import torch
from PIL import Image
from transformers import (
AutoTokenizer,
AutoImageProcessor,
AutoModelForCausalLM,
)
url = "img.png"
messages = [{"role": "user", "content": [{"type": "image"}, {"type": "text", "text": "describe this image"}]}]
image = Image.open(url)
model_dir = "THUDM/glm-edge-v-5b"
processor = AutoImageProcessor.from_pretrained(model_dir, trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained(model_dir, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
model_dir,
torch_dtype=torch.bfloat16,
device_map="auto",
trust_remote_code=True,
)
inputs = tokenizer.apply_chat_template(
messages, add_generation_prompt=True, return_dict=True, tokenize=True, return_tensors="pt"
).to(next(model.parameters()).device)
generate_kwargs = {
**inputs,
"pixel_values": torch.tensor(processor(image).pixel_values).to(next(model.parameters()).device),
}
output = model.generate(**generate_kwargs, max_new_tokens=100)
print(tokenizer.decode(output[0][len(inputs["input_ids"][0]):], skip_special_tokens=True))
```
## 协议
本模型的权重的使用则需要遵循 [LICENSE](LICENSE)。