Image-Text-to-Text
Transformers
Safetensors
kimi_k3
feature-extraction
compressed-tensors
conversational
custom_code
Instructions to use SinterForge/Kimi-K3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SinterForge/Kimi-K3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="SinterForge/Kimi-K3", trust_remote_code=True) 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 AutoModel model = AutoModel.from_pretrained("SinterForge/Kimi-K3", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use SinterForge/Kimi-K3 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SinterForge/Kimi-K3" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SinterForge/Kimi-K3", "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/SinterForge/Kimi-K3
- SGLang
How to use SinterForge/Kimi-K3 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 "SinterForge/Kimi-K3" \ --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": "SinterForge/Kimi-K3", "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 "SinterForge/Kimi-K3" \ --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": "SinterForge/Kimi-K3", "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 SinterForge/Kimi-K3 with Docker Model Runner:
docker model run hf.co/SinterForge/Kimi-K3
| { | |
| "architectures": [ | |
| "KimiK3ForConditionalGeneration" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_kimi_k3.KimiK3Config", | |
| "AutoModel": "modeling_kimi_k3.KimiK3ForConditionalGeneration", | |
| "AutoModelForCausalLM": "modeling_kimi_k3.KimiK3ForConditionalGeneration" | |
| }, | |
| "bos_token_id": 163584, | |
| "dtype": "bfloat16", | |
| "eos_token_id": 163586, | |
| "ignore_index": -100, | |
| "image_placeholder": "<|kimi_image_placeholder|>", | |
| "media_placeholder_token_id": 163605, | |
| "model_type": "kimi_k3", | |
| "pad_token_id": 163839, | |
| "text_config": { | |
| "_name_or_path": "", | |
| "activation_situ_beta": 4.0, | |
| "activation_situ_linear_beta": 25.0, | |
| "add_cross_attention": false, | |
| "architectures": [ | |
| "KimiLinearForCausalLM" | |
| ], | |
| "attn_res_block_size": 12, | |
| "auto_map": { | |
| "AutoConfig": "configuration_kimi_k3.KimiLinearConfig", | |
| "AutoModel": "modeling_kimi_linear.KimiLinearModel", | |
| "AutoModelForCausalLM": "modeling_kimi_linear.KimiLinearForCausalLM" | |
| }, | |
| "bad_words_ids": null, | |
| "begin_suppress_tokens": null, | |
| "bos_token_id": 163584, | |
| "chunk_size_feed_forward": 0, | |
| "cross_attention_hidden_size": null, | |
| "decoder_start_token_id": null, | |
| "diversity_penalty": 0.0, | |
| "do_sample": false, | |
| "dtype": "bfloat16", | |
| "early_stopping": false, | |
| "encoder_no_repeat_ngram_size": 0, | |
| "eos_token_id": 163586, | |
| "exponential_decay_length_penalty": null, | |
| "finetuning_task": null, | |
| "first_k_dense_replace": 1, | |
| "forced_bos_token_id": null, | |
| "forced_eos_token_id": null, | |
| "hidden_act": "situ", | |
| "hidden_size": 7168, | |
| "id2label": { | |
| "0": "LABEL_0", | |
| "1": "LABEL_1" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 33792, | |
| "is_decoder": false, | |
| "is_encoder_decoder": false, | |
| "kv_lora_rank": 512, | |
| "label2id": { | |
| "LABEL_0": 0, | |
| "LABEL_1": 1 | |
| }, | |
| "latent_moe_use_norm": true, | |
| "length_penalty": 1.0, | |
| "linear_attn_config": { | |
| "full_attn_layers": [ | |
| 4, | |
| 8, | |
| 12, | |
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| ], | |
| "gate_lower_bound": -5.0, | |
| "head_dim": 128, | |
| "kda_layers": [ | |
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| ], | |
| "num_heads": 96, | |
| "short_conv_kernel_size": 4, | |
| "use_full_rank_gate": true | |
| }, | |
| "max_length": 20, | |
| "max_position_embeddings": 1048576, | |
| "min_length": 0, | |
| "mla_use_nope": true, | |
| "mla_use_output_gate": true, | |
| "model_type": "kimi_linear", | |
| "moe_intermediate_size": 3072, | |
| "moe_layer_freq": 1, | |
| "moe_renormalize": true, | |
| "moe_router_activation_func": "sigmoid", | |
| "no_repeat_ngram_size": 0, | |
| "num_attention_heads": 96, | |
| "num_beam_groups": 1, | |
| "num_beams": 1, | |
| "num_expert_group": 1, | |
| "num_experts": 896, | |
| "num_experts_per_token": 16, | |
| "num_hidden_layers": 93, | |
| "num_key_value_heads": 96, | |
| "num_nextn_predict_layers": 0, | |
| "num_return_sequences": 1, | |
| "num_shared_experts": 2, | |
| "output_attentions": false, | |
| "output_hidden_states": false, | |
| "output_scores": false, | |
| "pad_token_id": 163839, | |
| "prefix": null, | |
| "problem_type": null, | |
| "pruned_heads": {}, | |
| "q_lora_rank": 1536, | |
| "qk_nope_head_dim": 128, | |
| "qk_rope_head_dim": 64, | |
| "quantization_config": { | |
| "config_groups": { | |
| "group_0": { | |
| "format": "mxfp4-pack-quantized", | |
| "input_activations": null, | |
| "output_activations": null, | |
| "targets": [ | |
| "Linear" | |
| ], | |
| "weights": { | |
| "actorder": null, | |
| "block_structure": null, | |
| "dynamic": false, | |
| "group_size": 32, | |
| "num_bits": 4, | |
| "observer": "minmax", | |
| "observer_kwargs": {}, | |
| "scale_dtype": "torch.uint8", | |
| "strategy": "group", | |
| "symmetric": true, | |
| "type": "float", | |
| "zp_dtype": null | |
| } | |
| } | |
| }, | |
| "format": "mxfp4-pack-quantized", | |
| "global_compression_ratio": null, | |
| "ignore": [ | |
| "re:.*self_attn.*", | |
| "re:.*shared_experts.*", | |
| "re:.*mlp\\.(gate|up|gate_up|down)_proj.*", | |
| "re:.*lm_head.*", | |
| "re:.*vision_tower.*", | |
| "re:.*mm_projector.*" | |
| ], | |
| "kv_cache_scheme": null, | |
| "quant_method": "compressed-tensors", | |
| "quantization_status": "compressed" | |
| }, | |
| "remove_invalid_values": false, | |
| "repetition_penalty": 1.0, | |
| "return_dict": true, | |
| "return_dict_in_generate": false, | |
| "rms_norm_eps": 1e-05, | |
| "routed_expert_hidden_size": 3584, | |
| "routed_scaling_factor": 1.0, | |
| "sep_token_id": null, | |
| "suppress_tokens": null, | |
| "task_specific_params": null, | |
| "temperature": 1.0, | |
| "tf_legacy_loss": false, | |
| "tie_encoder_decoder": false, | |
| "tie_word_embeddings": false, | |
| "tokenizer_class": null, | |
| "top_k": 50, | |
| "top_p": 1.0, | |
| "topk_group": 1, | |
| "topk_method": "noaux_tc", | |
| "torchscript": false, | |
| "transformers_version": "4.56.2", | |
| "typical_p": 1.0, | |
| "use_bfloat16": false, | |
| "use_cache": true, | |
| "use_grouped_topk": true, | |
| "v_head_dim": 128, | |
| "vocab_size": 163840 | |
| }, | |
| "tie_word_embeddings": false, | |
| "vision_config": { | |
| "_attn_implementation": "flash_attention_2", | |
| "activation_func": "gelu_pytorch_tanh", | |
| "attn_bias": false, | |
| "init_pos_emb_height": 64, | |
| "init_pos_emb_time": 4, | |
| "init_pos_emb_width": 64, | |
| "linear_bias": false, | |
| "merge_kernel_size": [ | |
| 2, | |
| 2 | |
| ], | |
| "merge_type": "sd2_tpool", | |
| "mlp_type": "mlp2", | |
| "mm_hidden_size": 1024, | |
| "mm_projector_type": "patchmergerv2", | |
| "norm_type": "rmsnorm", | |
| "patch_embed_proj_bias": false, | |
| "patch_size": 14, | |
| "pos_emb_interpolation_mode": "bilinear", | |
| "pos_emb_type": "divided_fixed", | |
| "projector_hidden_act": "gelu", | |
| "projector_ln_eps": 1e-05, | |
| "qkv_hidden_size": 1536, | |
| "text_hidden_size": 7168, | |
| "vt_hidden_size": 1024, | |
| "vt_intermediate_size": 4096, | |
| "vt_num_attention_heads": 12, | |
| "vt_num_hidden_layers": 27 | |
| } | |
| } |