Downloads · 30 days
15
15% of all-time downloads
trohrbaugh/ZAYA1-74B-preview-heretic
ZAYA1-74B-preview-heretic is a machine learning model from trohrbaugh. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Downloads · 30 days
15
15% of all-time downloads
All-time downloads
98
Public
Parameters
74.8B
150 GB on disk
Likes
1
Public
Click a slice to open those files.
.safetensors150 GB · 100%
How the weights are stored.
BF1674.8B · 100%
From the Hugging Face model README
| Parameter | Value |
|---|---|
| start_layer_index | 43 |
| end_layer_index | 72 |
| preserve_good_behavior_weight | 0.5780 |
| steer_bad_behavior_weight | 0.0005 |
| overcorrect_relative_weight | 0.9917 |
| neighbor_count | 5 |
| Metric | This model | Original model (Zyphra/ZAYA1-74B-preview) |
|---|---|---|
| KL divergence | 0.0087 | 0 (by definition) |
| Refusals | 1/100 | 96/100 |
ZAYA1-74B-Preview is a mixture of experts language model with 4B active and 74B total parameters. This is a reasoning-base checkpoint which has not been tuned for chat or undergone RL post-training. ZAYA1-74B-Preview was trained end to end on AMD.
Learn more on our blog.
We recommend installing the following libraries in a fresh python environment (tested with python 3.12).
To use ZAYA1-74B-preview, install zaya1-pr branch from our fork of vllm library (the command will trigger a full build of vLLM from source):
pip install "vllm @ git+https://github.com/Zyphra/vllm.git@zaya1-pr"
If you want to run in transformers, install zaya1 branch from our fork of transformers library as well:
pip install "transformers @ git+https://github.com/Zyphra/transformers.git@zaya1"
To start vLLM server, run the following command:
vllm serve Zyphra/ZAYA1-74B-Preview --port 8010 \
--mamba-cache-dtype float32 --dtype bfloat16 \
--reasoning-parser qwen3 --enable-auto-tool-choice --tool-call-parser zaya_xml
For parallel deployment we recommend using DP with EP as TP for CCA is not supported in the branch above. If running on 8 GPUs, set extra flags -dp 8 -ep to run with DP=EP=8.
Once the server is up, you can query a model with curl like in the following example:
curl http://localhost:8010/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "Zyphra/ZAYA1-74B-Preview",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello. How is it going?"}
]
}'