Image-Text-to-Text
Transformers
Safetensors
multilingual
deepseek_vl_v2
feature-extraction
deepseek
vision-language
ocr
custom_code
Eval Results
Instructions to use deepseek-ai/DeepSeek-OCR-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepseek-ai/DeepSeek-OCR-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="deepseek-ai/DeepSeek-OCR-2", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("deepseek-ai/DeepSeek-OCR-2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use deepseek-ai/DeepSeek-OCR-2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "deepseek-ai/DeepSeek-OCR-2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "deepseek-ai/DeepSeek-OCR-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/deepseek-ai/DeepSeek-OCR-2
- SGLang
How to use deepseek-ai/DeepSeek-OCR-2 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 "deepseek-ai/DeepSeek-OCR-2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "deepseek-ai/DeepSeek-OCR-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "deepseek-ai/DeepSeek-OCR-2" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "deepseek-ai/DeepSeek-OCR-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use deepseek-ai/DeepSeek-OCR-2 with Docker Model Runner:
docker model run hf.co/deepseek-ai/DeepSeek-OCR-2
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"_name_or_path": "deepseek-ai/DeepSeek-OCR-2",
"candidate_resolutions": [
[
1024,
1024
]
],
"global_view_pos": "head",
"architectures": [
"DeepseekOCR2ForCausalLM"
],
"auto_map": {
"AutoConfig": "modeling_deepseekocr2.DeepseekOCR2Config",
"AutoModel": "modeling_deepseekocr2.DeepseekOCR2ForCausalLM"
},
"language_config": {
"architectures": [
"DeepseekV2ForCausalLM"
],
"auto_map": {
"AutoConfig": "configuration_deepseekv2.DeepseekV2Config",
"AutoModel": "modeling_deepseek.DeepseekV2Model",
"AutoModelForCausalLM": "modeling_deepseek.DeepseekV2ForCausalLM"
},
"bos_token_id": 0,
"eos_token_id": 1,
"first_k_dense_replace": 1,
"hidden_size": 1280,
"intermediate_size": 6848,
"kv_lora_rank": null,
"lm_head": true,
"max_position_embeddings": 8192,
"moe_intermediate_size": 896,
"n_group": 1,
"n_routed_experts": 64,
"n_shared_experts": 2,
"num_attention_heads": 10,
"num_experts_per_tok": 6,
"num_hidden_layers": 12,
"num_key_value_heads": 10,
"q_lora_rank": null,
"qk_nope_head_dim": 0,
"qk_rope_head_dim": 0,
"rm_head": false,
"topk_group": 1,
"topk_method": "greedy",
"torch_dtype": "bfloat16",
"use_mla": false,
"v_head_dim": 0,
"vocab_size": 129280
},
"model_type": "deepseek_vl_v2",
"projector_config": {
"input_dim": 896,
"model_type": "mlp_projector",
"n_embed": 1280,
"projector_type": "linear"
},
"tile_tag": "2D",
"torch_dtype": "bfloat16",
"transformers_version": "4.46.3",
"vision_config": {
"image_size": 1024,
"mlp_ratio": 3.7362,
"model_name": "deepencoderv2",
"model_type": "vision",
"width": {
"qwen2-0-5b": {
"dim": 896
},
"sam_vit_b": {
"downsample_channels": [
512,
1024
],
"global_attn_indexes": [
2,
5,
8,
11
],
"heads": 12,
"layers": 12,
"width": 768
}
}
},
"bos_token_id": 0,
"eos_token_id": 1,
"first_k_dense_replace": 1,
"hidden_size": 1280,
"intermediate_size": 6848,
"kv_lora_rank": null,
"lm_head": true,
"max_position_embeddings": 8192,
"moe_intermediate_size": 896,
"n_group": 1,
"n_routed_experts": 64,
"n_shared_experts": 2,
"num_attention_heads": 10,
"num_experts_per_tok": 6,
"num_hidden_layers": 12,
"num_key_value_heads": 10,
"q_lora_rank": null,
"qk_nope_head_dim": 0,
"qk_rope_head_dim": 0,
"rm_head": false,
"topk_group": 1,
"topk_method": "greedy",
"use_mla": false,
"v_head_dim": 0,
"vocab_size": 129280
} |