
This is a beginner's test model.

```
from transformers import AutoTokenizer, AutoModelForCausalLM
import transformers
import torch
modelName='MingZhuang/mz_model_merged'
model = AutoModelForCausalLM.from_pretrained(modelName)
tokenizer = AutoTokenizer.from_pretrained(modelName)
generate = transformers.pipeline(
    "text-generation",
    model=model,
    tokenizer=tokenizer,
)

Result = generate(
    "</s>Human: How can I find a girlfriend?<s> Assistant:",
    max_new_tokens=120
)
Result
```
{"language": ["en", "zh"], "license": "apache-2.0", "datasets": ["timdettmers/openassistant-guanaco"], "pipeline_tag": "text-generation", "Tags": ["Chat"], "widget": [{"text": "How can I find a girlfriend?", "example_title": "How can I find a girlfriend"}, {"text": "\u4f60\u5403\u4ec0\u4e48?", "example_title": "\u4f60\u5403\u4ec0\u4e48?"}]}
transformers safetensors blenderbot text-generation en zh dataset:timdettmers/openassistant-guanaco license:apache-2.0 autotrain_compatible endpoints_compatible region:us