Image-Text-to-Text
Transformers
kimi_k3
feature-extraction
compressed-tensors
conversational
custom_code
Instructions to use PYTHAI/Kimi-K3-fork with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PYTHAI/Kimi-K3-fork with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="PYTHAI/Kimi-K3-fork", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("PYTHAI/Kimi-K3-fork", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use PYTHAI/Kimi-K3-fork with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "PYTHAI/Kimi-K3-fork" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "PYTHAI/Kimi-K3-fork", "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/PYTHAI/Kimi-K3-fork
- SGLang
How to use PYTHAI/Kimi-K3-fork 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 "PYTHAI/Kimi-K3-fork" \ --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": "PYTHAI/Kimi-K3-fork", "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 "PYTHAI/Kimi-K3-fork" \ --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": "PYTHAI/Kimi-K3-fork", "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 PYTHAI/Kimi-K3-fork with Docker Model Runner:
docker model run hf.co/PYTHAI/Kimi-K3-fork
Download tokenizer_config.json from PYTHAI/Kimi-K3-fork: direct link, hf CLI and curl.
- Browser
- Download file 3.48 kB
-
https://huggingface.co/PYTHAI/Kimi-K3-fork/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://PYTHAI/Kimi-K3-fork/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/PYTHAI/Kimi-K3-fork/resolve/main/tokenizer_config.json
3.48 kB
| { | |
| "added_tokens_decoder": { | |
| "163584": { | |
| "content": "[BOS]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "163585": { | |
| "content": "[EOS]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "163586": { | |
| "content": "<|end_of_msg|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "163587": { | |
| "content": "<|open|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "163588": { | |
| "content": "<|close|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "163589": { | |
| "content": "<|sep|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": false | |
| }, | |
| "163590": { | |
| "content": "[start_header_id]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "163591": { | |
| "content": "[end_header_id]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "163593": { | |
| "content": "[EOT]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "163602": { | |
| "content": "<|media_begin|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "163603": { | |
| "content": "<|media_content|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "163604": { | |
| "content": "<|media_end|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "163605": { | |
| "content": "<|media_pad|>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "163649": { | |
| "content": "<osagent_mode>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "163838": { | |
| "content": "[UNK]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| }, | |
| "163839": { | |
| "content": "[PAD]", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "additional_special_tokens": [ | |
| "<|end_of_msg|>", | |
| "[start_header_id]", | |
| "[end_header_id]", | |
| "[EOT]", | |
| "<|media_begin|>", | |
| "<|media_content|>", | |
| "<|media_end|>", | |
| "<|media_pad|>", | |
| "<osagent_mode>" | |
| ], | |
| "bos_token": "[BOS]", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "[EOS]", | |
| "extra_special_tokens": {}, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "[PAD]", | |
| "tokenizer_class": "TikTokenTokenizer", | |
| "unk_token": "[UNK]", | |
| "auto_map": { | |
| "AutoTokenizer": [ | |
| "tokenization_kimi.TikTokenTokenizer", | |
| null | |
| ] | |
| } | |
| } |