Instructions to use ecloudtech/Erk-Linear with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ecloudtech/Erk-Linear with Transformers:

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

pipe = pipeline("text-generation", model="ecloudtech/Erk-Linear", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("ecloudtech/Erk-Linear", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ecloudtech/Erk-Linear with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/ecloudtech/Erk-Linear

SGLang

How to use ecloudtech/Erk-Linear 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 "ecloudtech/Erk-Linear" \
    --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": "ecloudtech/Erk-Linear",
		"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 "ecloudtech/Erk-Linear" \
        --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": "ecloudtech/Erk-Linear",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use ecloudtech/Erk-Linear with Docker Model Runner:
```
docker model run hf.co/ecloudtech/Erk-Linear
```

aigencydev commited on 5 days ago

Commit

bd06532

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1 Parent(s): 43fc5b4

Update README.md

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@@ -1,15 +1,31 @@
 ---
 license: apache-2.0
-base_model: Qwen/Qwen3-14B
 language:
   - tr
 tags:
   - linear-attention
   - gated-deltanet
   - hybrid-attention
   - turkish
   - erk
 inference: false
 ---
 # Erk-Linear

 ---
 license: apache-2.0
+base_model:
+  - ecloudtech/Erk-14B
+  - Qwen/Qwen3-14B
 language:
   - tr
 tags:
   - linear-attention
   - gated-deltanet
   - hybrid-attention
+  - efficient-attention
   - turkish
   - erk
+  - research
 inference: false
+model-index:
+  - name: Erk-Linear
+    results:
+      - task:
+          type: text-generation
+        dataset:
+          name: TurkishMMLU
+          type: turkishmmlu
+        metrics:
+          - type: accuracy
+            value: 68.1
+            name: "TurkishMMLU held-out 750 (oracle 68.8 — fark istatistiksel olarak anlamli degil, %95 GA [-2.9, +1.7])"
 ---
 # Erk-Linear