Instructions to use z-lab/Kimi-K2.5-DFlash with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use z-lab/Kimi-K2.5-DFlash with Transformers:

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

pipe = pipeline("text-generation", model="z-lab/Kimi-K2.5-DFlash", trust_remote_code=True)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("z-lab/Kimi-K2.5-DFlash", trust_remote_code=True)
model = AutoModel.from_pretrained("z-lab/Kimi-K2.5-DFlash", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use z-lab/Kimi-K2.5-DFlash with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "z-lab/Kimi-K2.5-DFlash"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "z-lab/Kimi-K2.5-DFlash",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/z-lab/Kimi-K2.5-DFlash

SGLang

How to use z-lab/Kimi-K2.5-DFlash 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 "z-lab/Kimi-K2.5-DFlash" \
    --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": "z-lab/Kimi-K2.5-DFlash",
		"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 "z-lab/Kimi-K2.5-DFlash" \
        --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": "z-lab/Kimi-K2.5-DFlash",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use z-lab/Kimi-K2.5-DFlash with Docker Model Runner:
```
docker model run hf.co/z-lab/Kimi-K2.5-DFlash
```

jianchen0311 commited on Apr 9

Commit

f49ec05

verified ·

1 Parent(s): 817dbc5

Upload draft checkpoint from draft-step-53000

Browse files

Files changed (4) hide show

config.json +1 -2
model-00001-of-00003.safetensors +1 -1
model-00002-of-00003.safetensors +1 -1
model-00003-of-00003.safetensors +1 -1

config.json CHANGED Viewed

@@ -6,7 +6,6 @@
   "attention_dropout": 0.0,
   "block_size": 16,
   "dflash_config": {
-    "mask_token_id": 163838,
     "target_layer_ids": [
       1,
       12,
@@ -55,4 +54,4 @@
   "use_cache": true,
   "use_sliding_window": false,
   "vocab_size": 163840
-}

   "attention_dropout": 0.0,
   "block_size": 16,
   "dflash_config": {
     "target_layer_ids": [
       1,
       12,
   "use_cache": true,
   "use_sliding_window": false,
   "vocab_size": 163840
+}

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