Instructions to use openeurollm/kda-sigmoid-hybrid-1.3B-100B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use openeurollm/kda-sigmoid-hybrid-1.3B-100B with Transformers:

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

pipe = pipeline("text-generation", model="openeurollm/kda-sigmoid-hybrid-1.3B-100B", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("openeurollm/kda-sigmoid-hybrid-1.3B-100B", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use openeurollm/kda-sigmoid-hybrid-1.3B-100B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "openeurollm/kda-sigmoid-hybrid-1.3B-100B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "openeurollm/kda-sigmoid-hybrid-1.3B-100B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/openeurollm/kda-sigmoid-hybrid-1.3B-100B

SGLang

How to use openeurollm/kda-sigmoid-hybrid-1.3B-100B 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 "openeurollm/kda-sigmoid-hybrid-1.3B-100B" \
    --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": "openeurollm/kda-sigmoid-hybrid-1.3B-100B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "openeurollm/kda-sigmoid-hybrid-1.3B-100B" \
        --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": "openeurollm/kda-sigmoid-hybrid-1.3B-100B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use openeurollm/kda-sigmoid-hybrid-1.3B-100B with Docker Model Runner:
```
docker model run hf.co/openeurollm/kda-sigmoid-hybrid-1.3B-100B
```

kda-sigmoid-hybrid-1.3B-100B / config.json

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Add ComplexKDA 1.3B/100BT FineWeb-Edu model

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	{
	"architectures": [
	"ComplexKDAForCausalLM"
	],
	"model_type": "complex_kda",
	"auto_map": {
	"AutoConfig": "configuration_complex_kda.ComplexKDAConfig",
	"AutoModel": "modeling_complex_kda.ComplexKDAModel",
	"AutoModelForCausalLM": "modeling_complex_kda.ComplexKDAForCausalLM"
	},
	"attn_mode": "chunk",
	"hidden_size": 2048,
	"num_hidden_layers": 24,
	"num_heads": 16,
	"head_dim": 128,
	"intermediate_size": 5312,
	"hidden_ratio": null,
	"hidden_act": "swish",
	"vocab_size": 32000,
	"max_position_embeddings": 4096,
	"tie_word_embeddings": false,
	"norm_eps": 1e-06,
	"conv_size": 4,
	"use_short_conv": true,
	"fuse_norm": true,
	"fuse_swiglu": true,
	"fuse_cross_entropy": true,
	"initializer_range": 0.02,
	"allow_neg_eigval": false,
	"lower_bound": -5.0,
	"expand_v": 1.0,
	"gate": "sigmoid",
	"gate_init_style": "shipped",
	"output_gate": "lowrank",
	"attn": {
	"layers": [
	3,
	7,
	11,
	15,
	19,
	23
	],
	"num_heads": 16,
	"num_kv_heads": 16,
	"qkv_bias": false,
	"qk_norm": false,
	"output_gate": true,
	"use_rope": false,
	"rope_theta": 10000.0,
	"window_size": null
	},
	"drop_silu": true,
	"use_cache": true
	}