snapgate-surge

Snapgate Surge

Surge is a 7B model from Snapgate AI, purpose-built to help developers, creators, and everyday users with coding, website building, and a wide range of daily tasks in both Indonesian and English.

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✨ Key Capabilities

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📊 Model Specifications

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📈 Training Progress

Loss decreased from 0.031 to 0.019 — converging well over 1,000 steps.

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🚀 Usage

Python — Transformers

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_id  = "snapgate-ai/snapgate-surge"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model     = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype = torch.float16,
    device_map  = "auto"
)

SYSTEM_PROMPT = """You are Surge, an AI assistant from Snapgate AI (snapgate.tech).
You help users with coding, web development, and general questions
in both Indonesian and English."""

messages = [
    {"role": "system", "content": SYSTEM_PROMPT},
    {"role": "user",   "content": "Who are you?"},
]

inputs = tokenizer.apply_chat_template(
    messages,
    tokenize              = True,
    add_generation_prompt = True,
    return_tensors        = "pt"
).to(model.device)

outputs = model.generate(
    inputs,
    max_new_tokens = 512,
    temperature    = 0.7,
    top_p          = 0.9,
    do_sample      = True,
)

response = tokenizer.decode(outputs[0][inputs.shape[1]:], skip_special_tokens=True)
print(response)

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REST API — PHP

<?php
class SnapgateSurge {
    private string $apiUrl;

    public function __construct(string $apiUrl = 'http://your-server:8000') {
        $this->apiUrl = $apiUrl;
    }

    public function chat(string $message): string {
        $payload = json_encode([
            'messages'    => [['role' => 'user', 'content' => $message]],
            'max_tokens'  => 512,
            'temperature' => 0.7,
        ]);

        $ch = curl_init($this->apiUrl . '/v1/chat/completions');
        curl_setopt_array($ch, [
            CURLOPT_RETURNTRANSFER => true,
            CURLOPT_POST           => true,
            CURLOPT_POSTFIELDS     => $payload,
            CURLOPT_HTTPHEADER     => ['Content-Type: application/json'],
            CURLOPT_TIMEOUT        => 60,
        ]);

        $response = curl_exec($ch);
        curl_close($ch);

        $data = json_decode($response, true);
        return $data['choices'][0]['message']['content'] ?? 'Error';
    }
}

$surge    = new SnapgateSurge('http://your-server:8000');
$response = $surge->chat('Write a PHP function to validate an email address');
echo $response;

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Deploy with Ollama

curl -fsSL https://ollama.ai/install.sh | sh

cat > Modelfile << 'EOF'
FROM snapgate-ai/snapgate-surge
SYSTEM """You are Surge, an AI assistant from Snapgate AI (snapgate.tech).
You help users with coding, web development, and general questions."""
PARAMETER temperature 0.7
PARAMETER top_p 0.9
EOF

ollama create snapgate-surge -f Modelfile
ollama run snapgate-surge

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Deploy with vLLM (Production)

pip install vllm

python -m vllm.entrypoints.openai.api_server \
    --model snapgate-ai/snapgate-surge \
    --host 0.0.0.0 \
    --port 8000 \
    --max-model-len 2048

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💡 Example Conversation

English: