Instructions to use codeShare/joycaption_beta_one_SDNQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use codeShare/joycaption_beta_one_SDNQ with Transformers:

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

pipe = pipeline("image-text-to-text", model="codeShare/joycaption_beta_one_SDNQ")
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 AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("codeShare/joycaption_beta_one_SDNQ")
model = AutoModelForImageTextToText.from_pretrained("codeShare/joycaption_beta_one_SDNQ")
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?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use codeShare/joycaption_beta_one_SDNQ with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "codeShare/joycaption_beta_one_SDNQ"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "codeShare/joycaption_beta_one_SDNQ",
		"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/codeShare/joycaption_beta_one_SDNQ

SGLang

How to use codeShare/joycaption_beta_one_SDNQ 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 "codeShare/joycaption_beta_one_SDNQ" \
    --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": "codeShare/joycaption_beta_one_SDNQ",
		"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 "codeShare/joycaption_beta_one_SDNQ" \
        --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": "codeShare/joycaption_beta_one_SDNQ",
		"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 codeShare/joycaption_beta_one_SDNQ with Docker Model Runner:
```
docker model run hf.co/codeShare/joycaption_beta_one_SDNQ
```

codeShare commited on 18 days ago

Commit

e1a4ba4

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1 Parent(s): aeb9967

Delete config.json

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config.json +0 -88

config.json DELETED Viewed

@@ -1,88 +0,0 @@
-{
-  "architectures": [
-    "LlavaForConditionalGeneration"
-  ],
-  "dtype": "bfloat16",
-  "image_seq_length": 729,
-  "image_token_index": 128077,
-  "model_type": "llava",
-  "multimodal_projector_bias": true,
-  "projector_hidden_act": "gelu",
-  "quantization_config": {
-    "_load_in_4bit": true,
-    "_load_in_8bit": false,
-    "bnb_4bit_compute_dtype": "float16",
-    "bnb_4bit_quant_storage": "uint8",
-    "bnb_4bit_quant_type": "nf4",
-    "bnb_4bit_use_double_quant": false,
-    "llm_int8_enable_fp32_cpu_offload": false,
-    "llm_int8_has_fp16_weight": false,
-    "llm_int8_skip_modules": null,
-    "llm_int8_threshold": 6.0,
-    "load_in_4bit": true,
-    "load_in_8bit": false,
-    "quant_method": "bitsandbytes"
-  },
-  "text_config": {
-    "_name_or_path": "meta-llama/Llama-3.1-8B-Instruct",
-    "architectures": [
-      "LlamaForCausalLM"
-    ],
-    "attention_bias": false,
-    "attention_dropout": 0.0,
-    "bos_token_id": 128000,
-    "dtype": "bfloat16",
-    "eos_token_id": [
-      128001,
-      128008,
-      128009
-    ],
-    "head_dim": 128,
-    "hidden_act": "silu",
-    "hidden_size": 4096,
-    "initializer_range": 0.02,
-    "intermediate_size": 14336,
-    "max_position_embeddings": 131072,
-    "mlp_bias": false,
-    "model_type": "llama",
-    "num_attention_heads": 32,
-    "num_hidden_layers": 32,
-    "num_key_value_heads": 8,
-    "pad_token_id": null,
-    "pretraining_tp": 1,
-    "rms_norm_eps": 1e-05,
-    "rope_parameters": {
-      "factor": 8.0,
-      "high_freq_factor": 4.0,
-      "low_freq_factor": 1.0,
-      "original_max_position_embeddings": 8192,
-      "rope_theta": 500000.0,
-      "rope_type": "llama3"
-    },
-    "tie_word_embeddings": false,
-    "use_cache": true,
-    "vocab_size": 128256
-  },
-  "tie_word_embeddings": false,
-  "transformers_version": "5.0.0",
-  "vision_config": {
-    "_name_or_path": "google/siglip2-so400m-patch14-384",
-    "architectures": [
-      "SiglipVisionModel"
-    ],
-    "attention_dropout": 0.0,
-    "dtype": "bfloat16",
-    "hidden_act": "gelu_pytorch_tanh",
-    "hidden_size": 1152,
-    "image_size": 384,
-    "intermediate_size": 4304,
-    "layer_norm_eps": 1e-06,
-    "model_type": "siglip_vision_model",
-    "num_attention_heads": 16,
-    "num_channels": 3,
-    "num_hidden_layers": 27,
-    "patch_size": 14
-  },
-  "vision_feature_layer": -2,
-  "vision_feature_select_strategy": "full"
-}