Instructions to use ecloudtech/Erk-32B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ecloudtech/Erk-32B with Transformers:

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

pipe = pipeline("text-generation", model="ecloudtech/Erk-32B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

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

tokenizer = AutoTokenizer.from_pretrained("ecloudtech/Erk-32B")
model = AutoModelForCausalLM.from_pretrained("ecloudtech/Erk-32B", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ecloudtech/Erk-32B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ecloudtech/Erk-32B"
# 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-32B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ecloudtech/Erk-32B

SGLang

How to use ecloudtech/Erk-32B 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-32B" \
    --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-32B",
		"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-32B" \
        --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-32B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use ecloudtech/Erk-32B with Docker Model Runner:
```
docker model run hf.co/ecloudtech/Erk-32B
```

aigencydev commited on Sep 8

Commit

0ef5ac2

verified ·

1 Parent(s): b13571c

Kart: video kapak baglantisi

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README.md +4 -0

README.md CHANGED Viewed

@@ -158,6 +158,10 @@ Başarımlı Hesaplama Merkezi (UHeM)** altyapısında yürütüldü. Programın
 <video src="https://huggingface.co/ecloudtech/Erk-32B/resolve/main/assets/erk-32b-terminal.mp4" controls width="100%"></video>
 <table align="center"><tr>
 <td align="center"><a href="https://huggingface.co/ecloudtech/Erk-32B/resolve/main/assets/01-sonuc.png"><img src="https://huggingface.co/ecloudtech/Erk-32B/resolve/main/assets/01-sonuc.png" alt="Sonuç: %71,01, tabana göre +3,37" width="260"></a><br><sub>Sonuç</sub></td>
 <td align="center"><a href="https://huggingface.co/ecloudtech/Erk-32B/resolve/main/assets/02-egitim.png"><img src="https://huggingface.co/ecloudtech/Erk-32B/resolve/main/assets/02-egitim.png" alt="Eğitim künyesi" width="260"></a><br><sub>Eğitim künyesi</sub></td>

 <video src="https://huggingface.co/ecloudtech/Erk-32B/resolve/main/assets/erk-32b-terminal.mp4" controls width="100%"></video>
+<a href="https://huggingface.co/ecloudtech/Erk-32B/resolve/main/assets/erk-32b-terminal.mp4"><img src="https://huggingface.co/ecloudtech/Erk-32B/resolve/main/assets/erk-32b-terminal-kapak.png" alt="Terminal videosu — izlemek için tıklayın (67 sn, mp4)" width="100%"></a>
+<sub>Terminal kaydı, 67 sn — GitHub'da gömülü oynatıcı yoktur; görsele tıklayın.</sub>
 <table align="center"><tr>
 <td align="center"><a href="https://huggingface.co/ecloudtech/Erk-32B/resolve/main/assets/01-sonuc.png"><img src="https://huggingface.co/ecloudtech/Erk-32B/resolve/main/assets/01-sonuc.png" alt="Sonuç: %71,01, tabana göre +3,37" width="260"></a><br><sub>Sonuç</sub></td>
 <td align="center"><a href="https://huggingface.co/ecloudtech/Erk-32B/resolve/main/assets/02-egitim.png"><img src="https://huggingface.co/ecloudtech/Erk-32B/resolve/main/assets/02-egitim.png" alt="Eğitim künyesi" width="260"></a><br><sub>Eğitim künyesi</sub></td>