Image-Text-to-Text
Transformers
Safetensors
dots3_note
text-generation
tiny-random
multimodal
test-fixture
conversational
Instructions to use miraclezqc/TestForDots3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use miraclezqc/TestForDots3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="miraclezqc/TestForDots3") 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)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("miraclezqc/TestForDots3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use miraclezqc/TestForDots3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "miraclezqc/TestForDots3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "miraclezqc/TestForDots3", "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/miraclezqc/TestForDots3
- SGLang
How to use miraclezqc/TestForDots3 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 "miraclezqc/TestForDots3" \ --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": "miraclezqc/TestForDots3", "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 "miraclezqc/TestForDots3" \ --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": "miraclezqc/TestForDots3", "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 miraclezqc/TestForDots3 with Docker Model Runner:
docker model run hf.co/miraclezqc/TestForDots3
Download config.json from miraclezqc/TestForDots3: direct link, hf CLI and curl.
- Browser
- Download file 3.74 kB
-
https://huggingface.co/miraclezqc/TestForDots3/resolve/main/config.json
- Command line
-
hf download hf://miraclezqc/TestForDots3/config.json
-
curl -L -o config.json https://huggingface.co/miraclezqc/TestForDots3/resolve/main/config.json
3.74 kB
| { | |
| "architectures": [ | |
| "Dots3NoteForConditionalGeneration" | |
| ], | |
| "audio_config": { | |
| "adapter_input_size": 8, | |
| "adapter_output_size": 8, | |
| "attention_bias": true, | |
| "attention_dropout": 0.0, | |
| "conv_output_size": 2, | |
| "downsample_hidden_size": 2, | |
| "dropout": 0.0, | |
| "dtype": "bfloat16", | |
| "feature_size": 8, | |
| "head_dim": 8, | |
| "hidden_act": "silu", | |
| "hidden_size": 8, | |
| "hop_length": 160, | |
| "intermediate_size": 16, | |
| "max_position_embeddings": 128, | |
| "model_type": "dots3_note_audio_encoder", | |
| "num_attention_heads": 1, | |
| "num_hidden_layers": 1, | |
| "num_key_value_heads": 1, | |
| "rope_parameters": { | |
| "partial_rotary_factor": 0.5, | |
| "rope_theta": 10000.0, | |
| "rope_type": "default" | |
| }, | |
| "samples_per_token": 1280, | |
| "sampling_rate": 16000 | |
| }, | |
| "audio_token_id": 77, | |
| "dtype": "bfloat16", | |
| "image_token_id": 17, | |
| "model_type": "dots3_note", | |
| "text_config": { | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 0, | |
| "dtype": "bfloat16", | |
| "eos_token_id": 25, | |
| "head_dim": 4, | |
| "hidden_act": "silu", | |
| "hidden_size": 8, | |
| "index_head_dim": 8, | |
| "index_n_heads": 2, | |
| "index_topk": 4, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 16, | |
| "kv_lora_rank": 2, | |
| "layer_types": [ | |
| "indexed_attention", | |
| "indexed_attention", | |
| "sliding_attention" | |
| ], | |
| "max_position_embeddings": 512, | |
| "mlp_bias": false, | |
| "mlp_layer_types": [ | |
| "dense", | |
| "sparse", | |
| "sparse" | |
| ], | |
| "model_type": "dots3_note_text", | |
| "moe_intermediate_size": 4, | |
| "n_group": 1, | |
| "n_routed_experts": 3, | |
| "n_shared_experts": 1, | |
| "norm_topk_prob": true, | |
| "num_attention_heads": 2, | |
| "num_experts_per_tok": 2, | |
| "num_hidden_layers": 3, | |
| "num_key_value_heads": 2, | |
| "output_router_logits": false, | |
| "pad_token_id": 16, | |
| "per_layer_config": { | |
| "2": { | |
| "head_dim": 8, | |
| "kv_lora_rank": 4, | |
| "num_attention_heads": 1, | |
| "num_key_value_heads": 1, | |
| "qk_nope_head_dim": 6 | |
| } | |
| }, | |
| "q_lora_rank": 4, | |
| "qk_nope_head_dim": 2, | |
| "qk_rope_head_dim": 2, | |
| "rms_norm_eps": 1e-05, | |
| "rope_parameters": { | |
| "indexed_attention": { | |
| "partial_rotary_factor": 0.5, | |
| "rope_theta": 80000000.0, | |
| "rope_type": "default" | |
| }, | |
| "sliding_attention": { | |
| "partial_rotary_factor": 0.25, | |
| "rope_theta": 50000.0, | |
| "rope_type": "default" | |
| } | |
| }, | |
| "routed_scaling_factor": 1.0, | |
| "shared_experts_intermediate_size": 4, | |
| "sliding_window": 4, | |
| "tie_word_embeddings": false, | |
| "topk_group": 1, | |
| "use_cache": true, | |
| "v_head_dim": 4, | |
| "vocab_size": 341 | |
| }, | |
| "tie_word_embeddings": false, | |
| "transformers_version": "5.19.0.dev0", | |
| "video_token_id": 37, | |
| "vision_config": { | |
| "adapter_in_dim": 8, | |
| "adapter_merge_size": 2, | |
| "adapter_out_dim": 8, | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "dtype": "bfloat16", | |
| "embed_dim": 8, | |
| "hidden_act": "silu", | |
| "hidden_size": 8, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 16, | |
| "mlp_bias": false, | |
| "mlp_layer_types": [ | |
| "dense", | |
| "sparse", | |
| "sparse" | |
| ], | |
| "model_type": "dots3_note_vision_encoder", | |
| "moe_intermediate_size": 4, | |
| "num_attention_heads": 2, | |
| "num_channels": 3, | |
| "num_experts_per_tok": 2, | |
| "num_hidden_layers": 3, | |
| "num_local_experts": 3, | |
| "patch_size": 2, | |
| "per_layer_config": { | |
| "2": { | |
| "num_local_experts": 4 | |
| } | |
| }, | |
| "rms_norm_eps": 1e-05, | |
| "rope_parameters": { | |
| "rope_theta": 10000.0, | |
| "rope_type": "axial" | |
| }, | |
| "router_scaling_factor": 1.0, | |
| "spatial_merge_size": 2 | |
| } | |
| } | |