HackerNet-Beta v1

⚠️ Research only. This model is trained for cybersecurity research and authorized penetration testing.

Architecture

Parameter	Value
Hidden Dim	768
Layers	16
Attention Heads	12
KV Heads (GQA)	4
MoE Experts	4 (top-2)
Vocab Size	32,768
Max Seq Len	4,096
BitNet	✅ Enabled

Training

Setting	Value
Final Avg Loss	`0.0000`
Learning Rate	`0.0001`
Gradient Accumulation	4 steps
Max Length	1024 tokens
Precision	float16 + AMP
Epochs	4

Datasets Trained On

OpenAssistant/oasst_top1_2023-08-25
ai4bharat/indic-instruct-data-v0.1
HydraLM/hindi_multiturn_conversations
uonlp/CulturaX
HydraLM/hinglish_multiturn_conversations
festvox/cmu_indic
HuggingFaceH4/ultrachat_200k
teknium/OpenHermes-2.5

Versioning

File	Description
`hackernet_v1.pt`	PyTorch state dict
`hackernet_v1.safetensors`	Safetensors format
`versions/v1/config.json`	Architecture config

Usage

import torch
from core.model import HackerNetModel
from core.config import get_optimal_config

config = get_optimal_config()
model = HackerNetModel(config)
model.load_state_dict(torch.load("hackernet_v1.pt", map_location="cpu"))
model.eval()

Auto-generated by HackerNet training pipeline on Lightning AI

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