| | --- |
| | language: en |
| | license: apache-2.0 |
| | tags: |
| | - text-generation |
| | - zen |
| | - zenlm |
| | - hanzo |
| | - instruct |
| | - efficient |
| | pipeline_tag: text-generation |
| | library_name: transformers |
| | --- |
| | |
| | # Zen Eco Instruct |
| |
|
| | Efficient instruction-tuned language model for general-purpose tasks. |
| |
|
| | ## Overview |
| |
|
| | Built on **Zen MoDE (Mixture of Distilled Experts)** architecture with 4B parameters and 32K context window. |
| |
|
| | Developed by [Hanzo AI](https://hanzo.ai) and the [Zoo Labs Foundation](https://zoo.ngo). |
| |
|
| | ## Quick Start |
| |
|
| | ```python |
| | from transformers import AutoModelForCausalLM, AutoTokenizer |
| | |
| | model_id = "zenlm/zen-eco-instruct" |
| | tokenizer = AutoTokenizer.from_pretrained(model_id) |
| | model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto") |
| | |
| | messages = [{"role": "user", "content": "Hello!"}] |
| | text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
| | inputs = tokenizer([text], return_tensors="pt").to(model.device) |
| | outputs = model.generate(**inputs, max_new_tokens=512) |
| | print(tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)) |
| | ``` |
| |
|
| | ## API Access |
| |
|
| | ```bash |
| | curl https://api.hanzo.ai/v1/chat/completions \ |
| | -H "Authorization: Bearer $HANZO_API_KEY" \ |
| | -H "Content-Type: application/json" \ |
| | -d '{"model": "zen-eco-instruct", "messages": [{"role": "user", "content": "Hello"}]}' |
| | ``` |
| |
|
| | Get your API key at [console.hanzo.ai](https://console.hanzo.ai) — $5 free credit on signup. |
| |
|
| | ## Model Details |
| |
|
| | | Attribute | Value | |
| | |-----------|-------| |
| | | Parameters | 4B | |
| | | Architecture | Zen MoDE | |
| | | Context | 32K tokens | |
| | | License | Apache 2.0 | |
| |
|
| | ## License |
| |
|
| | Apache 2.0 |
| |
|
