Add branded Hologram model card
Browse files
README.md
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---
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license: mit
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base_model: microsoft/bitnet-b1.58-2B-4T
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pipeline_tag: text-generation
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inference: false
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tags:
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- hologram
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- q
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- kappa-object
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- holo
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- ternary
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- bitnet
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- llama3
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---
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<div align="center">
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# Hologram 路 BitNet-2B-4T
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**Native 1.58-bit ternary brain**
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`t2 路 1.58-bit ternary` 路 `0.69 GB` 路 streamed to Q as a **key-addressable `.holo` object**
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[Hologram](https://gethologram.ai) 路 [Live Space](https://huggingface.co/spaces/HOLOGRAMTECH/hologram) 路 [Organization](https://huggingface.co/HOLOGRAMTECH) 路 [Code](https://github.com/Hologram-Technologies)
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</div>
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---
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## What this is
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Microsoft's BitNet b1.58 2B4T, the first natively 1.58-bit trained model at scale, re-encoded to Hologram's ternary key format. Q's default brain: fast, tiny, and coherent.
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This repository is **not** a GGUF or Transformers checkpoint. It is a **Hologram key object**: the weights of `microsoft/bitnet-b1.58-2B-4T` re-encoded into Hologram's content-addressed `.holo` format so they stream, one verified block at a time, into **Q**, the on-device brain of the Hologram web OS. It runs in the browser on WebGPU, serverless, with nothing to install.
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## How it streams
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The object is laid out for cold streaming from an untrusted CDN:
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| File | Role |
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|---|---|
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| `manifest.json` | the root. Names every tensor and the key (content hash) of its block. |
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| `b/sha256_*.gz` | the tensor blocks. Each filename **is** the SHA-256 of its bytes. |
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| `tokenizer.gguf` | bundled header, so loading is fully serverless. |
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Q fetches the manifest, then pulls each block by its key and re-derives `sha256(block)` on arrival. If a byte is wrong, the block is rejected. Nothing is trusted; everything is proven.
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## Verify (Law L5)
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The object's identity is the SHA-256 of its manifest, pinned in Q's catalog before a single byte of weight is trusted:
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```
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did:holo:sha256:fcf835659d88d2fe6f683cf1ab8de6a6ba6214ea0deeee4b1bcf3da1a4c05412
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```
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```bash
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curl -sL https://huggingface.co/HOLOGRAMTECH/q-bitnet-2b/resolve/main/manifest.json | sha256sum
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```
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## Specifications
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| | |
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|---|---|
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| Architecture | BitNet b1.58 (Llama 3 template) |
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| Precision | t2 路 1.58-bit ternary |
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| Object size | 0.69 GB |
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| Hidden size | 2560 |
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| Layers | 30 |
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| Heads (Q / KV) | 20 / 5 (GQA) |
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| FFN | 6912 |
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| Vocab | 128256 |
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| Context | 3000 |
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| Format | `holo-2bit/1` |
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## Provenance and license
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Derived from [`microsoft/bitnet-b1.58-2B-4T`](https://huggingface.co/microsoft/bitnet-b1.58-2B-4T). Inherits the MIT license from microsoft/bitnet-b1.58-2B-4T. The re-encoding is content-addressed at the key level: the object either re-derives to its pinned identity or it is refused.
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## Run it
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These weights load through Q, not a standard runtime. Open the [Live Space](https://huggingface.co/spaces/HOLOGRAMTECH/hologram) or visit [gethologram.ai](https://gethologram.ai) to run Hologram, then pick **BitNet-2B-4T** from Q's model list.
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<div align="center"><sub>Composed on the golden ratio. One key, everything.</sub></div>
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