snapgate-surge-v3-moe

🚀 Snapgate Surge V3

Official AI Assistant of Snapgate AI

Model Surge V3 is the latest version of Snapgate Surge, fine-tuned on a custom conversation dataset to shape a consistent persona and response style for Snapgate AI.

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⚡ Model Specifications

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✨ Key Capabilities

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🚀 Usage

from unsloth import FastLanguageModel

model, tokenizer = FastLanguageModel.from_pretrained(
    model_name = "kadalicious22/snapgate-surge-v3-moe",
    max_seq_length = 2048,
    load_in_4bit = True,
)
FastLanguageModel.for_inference(model)

messages = [
    {"role": "system", "content": "You are Surge, an AI assistant from Snapgate AI."},
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
    messages, tokenize=True, add_generation_prompt=True, return_tensors="pt"
).to("cuda")

outputs = model.generate(input_ids=inputs, max_new_tokens=256, temperature=0.7, top_p=0.9)
print(tokenizer.decode(outputs[0][inputs.shape[1]:], skip_special_tokens=True))

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📊 Training Details

• Dataset: custom Snapgate AI conversations (identity, coding, general Q&A)
• Fine-tuning method: LoRA on top of a 4-bit quantized base model
• Checkpoints saved periodically to support resumable training

Training Progress

Training loss dropped sharply within the first ~100 steps and stabilized in the 0.008–0.01 range from step ~150 onward, indicating the model converged well on the training persona/style without significant further improvement past that point.

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🔗 Links

• Website: snapgate.tech