Add branded Hologram model card
Browse files
README.md
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---
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license: apache-2.0
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base_model: Qwen/Qwen2.5-Coder-7B-Instruct
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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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- code
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- agentic
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- qwen2
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---
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<div align="center">
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# Hologram 路 Qwen2.5-Coder-7B
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**Agentic coding brain**
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`q3f` 路 `3.4 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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The Holo Code agent brain. A self-contained key object: the tokenizer is bundled, so it loads with no external dependency and runs tool-using coding workflows.
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This repository is **not** a GGUF or Transformers checkpoint. It is a **Hologram key object**: the weights of `Qwen/Qwen2.5-Coder-7B-Instruct` 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 (where present), 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:sha256:539941cb060c7dd583e2e86697e53f2c5d511d597c65d09d9c780fbded2c3edf
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```
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```bash
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# the manifest hash equals the pinned identity above
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curl -sL https://huggingface.co/HOLOGRAMTECH/q-qwen-coder-7b/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 | Qwen2.5-Coder |
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| Precision | q3f |
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| Object size | 3.4 GB |
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| Hidden size | 3584 |
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| Layers | 28 |
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| Heads (Q / KV) | 28 / 4 (GQA) |
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| FFN | 18944 |
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| Vocab | 152064 |
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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 [`Qwen/Qwen2.5-Coder-7B-Instruct`](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct). The re-encoding is lossless-by-construction at the key level: every block is content-addressed, so 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 **Qwen2.5-Coder-7B** 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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