Instructions to use Zyphra/ZAYA1-VL-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Zyphra/ZAYA1-VL-8B with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="Zyphra/ZAYA1-VL-8B")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoModelForSeq2SeqLM
model = AutoModelForSeq2SeqLM.from_pretrained("Zyphra/ZAYA1-VL-8B", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Zyphra/ZAYA1-VL-8B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Zyphra/ZAYA1-VL-8B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Zyphra/ZAYA1-VL-8B",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/Zyphra/ZAYA1-VL-8B

SGLang

How to use Zyphra/ZAYA1-VL-8B with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Zyphra/ZAYA1-VL-8B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Zyphra/ZAYA1-VL-8B",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Zyphra/ZAYA1-VL-8B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Zyphra/ZAYA1-VL-8B",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use Zyphra/ZAYA1-VL-8B with Docker Model Runner:
```
docker model run hf.co/Zyphra/ZAYA1-VL-8B
```

ZAYA1-VL-8B / config.json

ganeshnanduru

Update config.json

fda6d21 verified 8 days ago

raw

history blame contribute delete

1.77 kB

	{
	"activation_func": "swiglu",
	"activation_func_fp8_input_store": false,
	"add_bias_linear": false,
	"apply_rope_fusion": true,
	"ar_threshold": 1,
	"architectures": [
	"Zaya1VLForConditionalGeneration"
	],
	"attention_bias": false,
	"bias_activation_fusion": true,
	"bos_token_id": 2,
	"cca": true,
	"clamp_temp": false,
	"eos_token_id": 262143,
	"ffn_hidden_size": 4096,
	"fused_add_norm": false,
	"gated_linear_unit": true,
	"hidden_size": 2048,
	"head_dim": 128,
	"image_token_id": 262147,
	"lm_head_bias": false,
	"lora_rank": 0,
	"max_position_embeddings": 32768,
	"model_type": "zaya1_vl",
	"moe_router_topk": 1,
	"norm_epsilon": 1e-05,
	"normalization": "RMSNorm",
	"num_attention_heads": 8,
	"num_experts": 16,
	"num_hidden_layers": 40,
	"num_key_value_heads": 2,
	"num_query_groups": 2,
	"pad_token_id": 0,
	"padding_side": "right",
	"projector_hidden_act": "gelu",
	"residual_in_fp32": false,
	"rope_pct": 0.5,
	"rotary_base": 1000000,
	"scale_residual_merge": true,
	"sliding_window": null,
	"temporal_patch_size": 1,
	"tie_word_embeddings": true,
	"torch_dtype": "bfloat16",
	"transformers_version": "4.57.1",
	"use_lora_att": false,
	"use_rope_scaling": false,
	"vision_config": {
	"_attn_implementation_autoset": true,
	"hidden_size": 1280,
	"in_chans": 3,
	"model_type": "qwen2_5_vl",
	"out_hidden_size": 2048,
	"spatial_patch_size": 14,
	"temporal_patch_size": 1,
	"tokens_per_second": 2,
	"torch_dtype": "bfloat16"
	},
	"vision_end_token_id": 256000,
	"vision_lora": true,
	"vision_lora_rank_attn": 8,
	"vision_lora_rank_mlp": 32,
	"vision_start_token_id": 255999,
	"vocab_size": 262272,
	"zaya_mlp_expansion": 256,
	"zaya_use_eda": true,
	"zaya_use_mod": true
	}