org card: quickstart with @thinletterio/vqweb

README.md

@@ -18,13 +18,13 @@ the WebGPU runtime, the verification recipe and every released file. Web: [thinl
 ## Quickstart: a released client in your page
 
 ```js
-import { loadVqwClient } from 'https://thinletter.io/vqweb/vqweb.js';   // or: npm install @thinletter/vqweb
+import { loadVqwClient } from 'https://thinletter.io/vqweb/vqweb.js';   // or: npm install @thinletterio/vqweb
 
 const client = await loadVqwClient('https://huggingface.co/thinletter/qwen3-embedding-0.6b-vq-clients/resolve/main/qwen3-0.6b-vq3.5d2-webfaq_q-vocfull.vqw');
 const q = await client.embed('Kolik stojí parkování v centru Prahy?');   // Float32Array(1024), L2-normalised: dot it with your Qwen3-Embedding-0.6B index
 ```
 
-`@thinletter/vqweb` ([npm](https://www.npmjs.com/package/@thinletter/vqweb), Apache-2.0) is the open WebGPU runtime as a package: download with
+`@thinletterio/vqweb` ([npm](https://www.npmjs.com/package/@thinletterio/vqweb), Apache-2.0) is the open WebGPU runtime as a package: download with
 progress, a cache in the browser's private file system, tokenizer and prompt from the container header, pipelines, warm-up. Needs WebGPU
 with `shader-f16` (Chrome / Edge), no CPU fallback; about 100 ms per query on an integrated GPU. The scalar GGUF files run with
 [wllama](https://github.com/ngxson/wllama) or llama.cpp.
@@ -54,7 +54,7 @@ The index does not change.
 | [demo](https://huggingface.co/spaces/thinletter/demo) (Space) | — | the browser demo, static | search SciDocs (25 656 abstracts) or WebFAQ-cs (71 529 Czech passages) locally with a scalar or a vector-quantised client; models and indexes download from thinletter.io |
 | [llm-weight-compression-evidence](https://huggingface.co/datasets/thinletter/llm-weight-compression-evidence) | dataset · MIT | per-window evidence | which objective a post-training quantiser should optimise (companion project) |
 
-Each model repository has a summary post in its Community tab with the numbers, what was found along the way, and the limits. The `.vqw` files load with `@thinletter/vqweb` (above); the GGUF files with llama.cpp / wllama.
+Each model repository has a summary post in its Community tab with the numbers, what was found along the way, and the limits. The `.vqw` files load with `@thinletterio/vqweb` (above); the GGUF files with llama.cpp / wllama.
 
 ## How we measure