# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("aolei/llm-chatglm2-ft", trust_remote_code=True, device_map="auto")Quick Links
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("aolei/llm-chatglm2-ft", trust_remote_code=True)
tokenizer.padding_side='left'
model = AutoModel.from_pretrained("LLaMA-Efficient-Tuning/t1_export", trust_remote_code=True).half().cuda()
model = model.eval()
response, history = model.chat(tokenizer, "给我一个折线图", history=[])
print(response, history)
- Downloads last month
- 9
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="aolei/llm-chatglm2-ft", trust_remote_code=True)