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64 lines
2.0 KiB
Markdown
64 lines
2.0 KiB
Markdown
<!--Copyright 2026 the HuggingFace Inc. team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
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specific language governing permissions and limitations under the License.
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⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
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rendered properly in your Markdown viewer.
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-->
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*This model was contributed to Hugging Face Transformers on 2026-07-01.*
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# ZAYA
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## Overview
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ZAYA1 is a 760M active / 8.4B total parameter MoE language model trained by Zyphra. It combines Compressed
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Convolutional Attention (CCA), a nonlinear ZAYA1 router, and residual scaling.
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ZAYA1 uses the Gemma 3 tokenizer. For more details, see the [ZAYA1 model card](https://huggingface.co/Zyphra/ZAYA1-8B)
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and Zyphra's technical reports.
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This model was contributed by [JJJYmmm](https://github.com/JJJYmmm).
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## Usage examples
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_id = "Zyphra/ZAYA1-8B"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
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inputs = tokenizer.apply_chat_template(
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[{"role": "user", "content": "Write a haiku about recursion in programming."}],
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tokenize=True,
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add_generation_prompt=True,
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enable_thinking=False,
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return_tensors="pt",
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)
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inputs = inputs.to(model.device)
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outputs = model.generate(**inputs, max_new_tokens=256)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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## ZayaConfig
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[[autodoc]] ZayaConfig
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## ZayaModel
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[[autodoc]] ZayaModel
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- forward
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## ZayaForCausalLM
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[[autodoc]] ZayaForCausalLM
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- forward
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