Wildnerve-tlm01 Model Checkpoints

This repository contains the trained weights for the Wildnerve-tlm01 hybrid neural-symbolic language model architecture, which combines transformer-based language processing with biologically-inspired Spike-Timing-Dependent Plasticity (STDP).

Repository Structure

The weights are organized into two main components:

snn/: Contains the STDP-trained synaptic weights that enable neuromorphic learning
- stdp_model_epoch_30.bin: Synaptic weights after 30 epochs of STDP training
transformer/: Contains the transformer model weights for language processing
- model_weights.bin: Transformer component weights

Usage

These weights are designed to be used with the Wildnerve-tlm01 model implementation located in the EvolphTech/Model repository.

Loading the Weights

import torch
import os
from huggingface_hub import hf_hub_download

# Download the components
snn_path = hf_hub_download(
    repo_id="EvolphTech/Checkpoints",
    filename="snn/stdp_model_epoch_30.bin",
    cache_dir="model_cache"
)

transformer_path = hf_hub_download(
    repo_id="EvolphTech/Checkpoints",
    filename="transformer/model_weights.bin",
    cache_dir="model_cache"
)

# Load the weights
snn_weights = torch.load(snn_path, map_location="cpu")
transformer_weights = torch.load(transformer_path, map_location="cpu")

For complete integration instructions, see the model documentation.

Training Details

SNN Component: Trained for 30 epochs using STDP learning rule with adaptive synaptic weights
Transformer Component: Trained on multiple programming and general knowledge datasets

License

Mozilla Public License 2.0 (MPL 2.0)