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-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xcczach/xturnix-pt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xcczach/xturnix-pt", 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-pt", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("xcczach/xturnix-pt", 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
Download tokenizer.json from xcczach/xturnix-pt: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/xcczach/xturnix-pt/resolve/main/tokenizer.json
- Command line
-
hf download hf://xcczach/xturnix-pt/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/xcczach/xturnix-pt/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 767c026082fb859f12de7a764a58ee2702f4722a8b60bef613b1ca3c1763582c
- Size of remote file:
- 11.4 MB
- SHA256:
- e1cdfc37289f88242660c6694e92e84dbbe3058b4cf45be593d784b658c0aa1d
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