Instructions to use LLM-OS-Models/gdn1-16k32k-bridge-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LLM-OS-Models/gdn1-16k32k-bridge-1b with Transformers:

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

pipe = pipeline("text-generation", model="LLM-OS-Models/gdn1-16k32k-bridge-1b", device_map="auto")

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("LLM-OS-Models/gdn1-16k32k-bridge-1b", dtype="auto", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use LLM-OS-Models/gdn1-16k32k-bridge-1b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LLM-OS-Models/gdn1-16k32k-bridge-1b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LLM-OS-Models/gdn1-16k32k-bridge-1b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/LLM-OS-Models/gdn1-16k32k-bridge-1b

SGLang

How to use LLM-OS-Models/gdn1-16k32k-bridge-1b 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 "LLM-OS-Models/gdn1-16k32k-bridge-1b" \
    --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": "LLM-OS-Models/gdn1-16k32k-bridge-1b",
		"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 "LLM-OS-Models/gdn1-16k32k-bridge-1b" \
        --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": "LLM-OS-Models/gdn1-16k32k-bridge-1b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use LLM-OS-Models/gdn1-16k32k-bridge-1b with Docker Model Runner:
```
docker model run hf.co/LLM-OS-Models/gdn1-16k32k-bridge-1b
```

gdn1-16k32k-bridge-1b / config.json

gyung

Upload GDN1 16K/32K Bridge 1B Full Fine-Tune

682e4c0 verified 26 days ago

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	{
	"allow_neg_eigval": false,
	"architectures": [
	"GatedDeltaNetForCausalLM"
	],
	"attn": null,
	"attn_mode": "chunk",
	"bos_token_id": 1,
	"conv_size": 4,
	"dtype": "bfloat16",
	"eos_token_id": 2,
	"expand_v": 1,
	"fuse_cross_entropy": true,
	"fuse_linear_cross_entropy": false,
	"fuse_norm": true,
	"fuse_swiglu": true,
	"head_dim": 256,
	"hidden_act": "swish",
	"hidden_ratio": 4,
	"hidden_size": 2048,
	"initializer_range": 0.02,
	"intermediate_size": null,
	"max_position_embeddings": 2048,
	"model_type": "gated_deltanet",
	"norm_eps": 1e-06,
	"norm_first": false,
	"num_heads": 4,
	"num_hidden_layers": 24,
	"num_v_heads": null,
	"pad_token_id": null,
	"tie_word_embeddings": true,
	"transformers_version": "5.5.4",
	"use_cache": false,
	"use_gate": true,
	"use_l2warp": false,
	"use_short_conv": false,
	"vocab_size": 32000
	}