| | --- |
| | license: apache-2.0 |
| | language: |
| | - en |
| | tags: |
| | - zen |
| | - zenlm |
| | - hanzo-ai |
| | - multilingual |
| | - translation |
| | - CJK |
| | pipeline_tag: text-generation |
| | library_name: transformers |
| | base_model: zenlm/zen-next-80b-instruct |
| | --- |
| | |
| | # Zen Multilingual |
| |
|
| | > **Parameters**: 32B | **Architecture**: Zen 3 Architecture | **Context**: 128K | **License**: Apache 2.0 | **Released**: 2024-12-01 |
| |
|
| | Multilingual generation across 30+ languages: English, Chinese, Japanese, Korean, Arabic, Spanish, French, German, Portuguese, Russian, and more. |
| |
|
| | Strong at cross-lingual reasoning, code-switching, and multilingual instruction following. |
| |
|
| | Base weights: [zenlm/zen-next-80b-instruct](https://huggingface.co/zenlm/zen-next-80b-instruct) |
| |
|
| | ```python |
| | from transformers import AutoModelForCausalLM, AutoTokenizer |
| | model = AutoModelForCausalLM.from_pretrained("zenlm/zen-next-80b-instruct", torch_dtype="auto") |
| | tokenizer = AutoTokenizer.from_pretrained("zenlm/zen-next-80b-instruct") |
| | messages = [{"role": "user", "content": "Your domain-specific prompt here"}] |
| | text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
| | inputs = tokenizer(text, return_tensors="pt").to(model.device) |
| | output = model.generate(**inputs, max_new_tokens=1024) |
| | print(tokenizer.decode(output[0][inputs.input_ids.shape[-1]:], skip_special_tokens=True)) |
| | ``` |
| |
|
| | --- |
| | ## The Zen LM Family |
| |
|
| | Joint research between **Hanzo AI** (Techstars '17), **Zoo Labs Foundation** (501c3), and **Lux Partners Limited**. |
| |
|
| | All weights Apache 2.0. Download, run locally, fine-tune, deploy commercially. |
| |
|
| | [HuggingFace](https://huggingface.co/zenlm) 路 [Chat](https://hanzo.chat) 路 [API](https://api.hanzo.ai) 路 [Docs](https://zenlm.org) |
| |
|