Getting Started

Getting Started

Install

[dependencies]
cortex-tensor = { git = "https://github.com/Limen-Neural/cortex-tensor", branch = "main" }

Optional Sentry:

cortex-tensor = { git = "...", features = ["sentry"] }

Tensor matmul

use cortex_tensor::tensor::ops::matmul;
use cortex_tensor::Tensor;

let a = Tensor::from_vec(vec![1.0, 2.0, 3.0, 4.0], &[2, 2]);
let b = Tensor::from_vec(vec![1.0, 0.0, 0.0, 1.0], &[2, 2]);
let c = matmul(&a, &b);
assert_eq!(c.shape(), &[2, 2]);

Transformer block

use cortex_tensor::transformer::{MultiHeadAttention, TransformerBlock};

let attn = MultiHeadAttention::new(/* dim */ 512, /* num_heads */ 8);
let block = TransformerBlock::new(/* dim */ 512, /* num_heads */ 8, /* mlp_dim */ 2048);

Tiny LM forward:

use cortex_tensor::transformer::{TransformerConfig, TransformerLM};

let model = TransformerLM::new(TransformerConfig::tiny());
let logits = model.forward(&[1u32, 42, 100, 7]);
// shape: [seq_len, vocab_size]

MoE router

use cortex_tensor::moe::{OlmoeRouter, RoutingMode};
use cortex_tensor::types::EMBEDDING_DIM;

// Stub (empty path) — no file needed
let mut router = OlmoeRouter::load_with_mode("", 8, 2, RoutingMode::StubUniform)?;
let out = router.forward(&vec![0.1; EMBEDDING_DIM])?;

// Real GGUF
let mut router = OlmoeRouter::load_with_mode(
    "path/to/model.gguf",
    0,  // 0 → use checkpoint expert_count
    0,  // 0 → use expert_used_count
    RoutingMode::DenseSim,
)?;
let emb = router.extract_token_embedding(42)?; // normalized to EMBEDDING_DIM
let out = router.forward(&emb)?;

forward expects length EMBEDDING_DIM (2048). Use extract_token_embedding or normalize/resample paths for other widths.

Build / test

cargo build
cargo test
cargo clippy --all-targets --all-features -- -D warnings
cargo fmt --all -- --check

Next

• Tensor
• MoE Router
• Parser Boundary

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Last updated: July 29, 2026 Updated by: Grok Build: Grok 4.5 Package tip reference: 37c5a21 (main)