1bit-MONSTER/ZAYA1-base-GGUF overview
ZAYA1 base — GGUF Our own GGUF conversion of Zyphra's ZAYA1 base https://huggingface.co/Zyphra/ZAYA1 base . It keeps Zyphra's original Megatron style checkpoin…
Runs locally from ~5.19 GB disk (8 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| ZAYA1-base-Q4_K_M.gguf | GGUF | Q4_K_M | 5.19 GB | Download |
Model Details
| Model ID | 1bit-MONSTER/ZAYA1-base-GGUF |
|---|---|
| Author | 1bit-MONSTER |
| Pipeline | — |
| License | apache-2.0 |
| Base model | Zyphra/ZAYA1-base |
| Last modified | 2026-09-27T14:42:18.000Z |
Model README
---
license: apache-2.0
base_model:
- Zyphra/ZAYA1-base
tags:
- gguf
- zaya
- moe
- base-model
---
ZAYA1-base — GGUF
Our own GGUF conversion of Zyphra's ZAYA1-base. It keeps Zyphra's original Megatron-style checkpoint layout, which transformers cannot load; our converter maps it to ZAYA's standard layout (llama.cpp #14). Converting Zyphra/ZAYA1-8B-legacy this way gives tensors byte-identical to the ones from Zyphra/ZAYA1-8B.
Contents
ZAYA1-base-Q4_K_M.gguf(8B shape: 40 layers, 16 experts; rope theta 1e6; 32,768-token context).
Validation
- Wikitext-2 test perplexity, 60 chunks of 512 tokens, Q4_K_M on Vulkan (Radeon 8060S): 8.53 ± 0.17.
- Raw-text perplexity favours base models; the post-trained ZAYA1-8B scores 32.13 on the same test.
Running it
With the 1bit engine:
1bit serve -m ZAYA1-base-Q4_K_M.gguf --device vulkan
ZAYA runs from our llama.cpp fork (branch 1bit/hrx-vulkan-patched); upstream llama.cpp has no ZAYA
model. The GGUFs must come from our converter: it writes the grouped convolution's weights
tap-major, which the graph expects.
Attribution
- Base model: Zyphra/ZAYA1-base, Apache 2.0.
- GGUF conversion and validation: the 1bit engine project, with the converter and model code in our llama.cpp fork.
- License: Apache 2.0, inherited from the base model.
Run 1bit-MONSTER/ZAYA1-base-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models