Text Classification
Transformers
Safetensors
Chinese
qwen3
text-generation
custom_code
turn-taking
turn-detection
spoken-dialogue
duplex-conversation
conversational
vllm
text-embeddings-inference
Instructions to use xcczach/xturnix-zh-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xcczach/xturnix-zh-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xcczach/xturnix-zh-base", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("xcczach/xturnix-zh-base", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("xcczach/xturnix-zh-base", trust_remote_code=True, device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
Add pipeline tag and paper link
#1
by nielsr HF Staff - opened
This PR adds pipeline_tag: text-classification to the model card metadata, so the model is properly categorized under text-classification. It also adds links to the paper page and the interactive demo/project page in the model card.
Thank you for contribution!
xcczach changed pull request status to merged