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README.md

@@ -34,7 +34,7 @@ tags:
 
 This repository holds the final pretrained checkpoint (step 90,000), an int8 ONNX export for on-device and browser runtimes, and the tokenizer.
 
-> **EchoMeBetter is not the only use case of KeelCore. It is a by-product.** EchoMeBetter, the browser extension, is the first product built on KeelCore: it runs KeelCore's text-rewriting adapters on your device. KeelCore itself is a general base model, and more adapters for different use cases are in progress.
+> **EchoMeBetter is not the only use case of KeelCore. It is a by-product.** EchoMeBetter, the browser extension, is the first product built on KeelCore: it runs KeelCore on your device.<!-- ADAPTERS (restore when the adapters are released): it runs KeelCore's text-rewriting adapters on your device. --> KeelCore itself is a general base model, and adapters for different use cases are in progress.<!-- ADAPTERS (restore when the adapters are released): KeelCore itself is a general base model, and more adapters for different use cases are in progress. -->
 
 * **Technical report:** <a href="https://saravanan-a-r.github.io/KeelCore/" target="_blank" rel="noopener noreferrer">https://saravanan-a-r.github.io/KeelCore/</a>
 * **Source code:** <a href="https://github.com/saravanan-a-r/KeelCore" target="_blank" rel="noopener noreferrer">https://github.com/saravanan-a-r/KeelCore</a>
@@ -112,7 +112,7 @@ To download only the ONNX files:
 snapshot_download("KeelCore/KeelCore-750M", allow_patterns=["onnx/int8/*"])
 ```
 
-That folder holds the base graphs, the tokenizer and `model.json`, and nothing from the PyTorch side is downloaded. Each entry under `adapters` in `model.json` names the adapter's folder and the hash of its `adapter.json`, which in turn lists the adapter's files with their hashes and the base it was trained on. The PyTorch weights are the other way round: the snippet above skips `onnx/`. Adapters are separate downloads from their own repositories, for example <a href="https://huggingface.co/KeelCore/KeelCore-750M-Professional" target="_blank" rel="noopener noreferrer">KeelCore-750M-Professional</a> (its `onnx/` folder).
+That folder holds the base graphs, the tokenizer and `model.json`, and nothing from the PyTorch side is downloaded. Each entry under `adapters` in `model.json` names the adapter's folder and the hash of its `adapter.json`, which in turn lists the adapter's files with their hashes and the base it was trained on. The PyTorch weights are the other way round: the snippet above skips `onnx/`. Adapters are separate downloads from their own repositories.<!-- ADAPTERS (restore when the adapters are released): Adapters are separate downloads from their own repositories, for example <a href="https://huggingface.co/KeelCore/KeelCore-750M-Professional" target="_blank" rel="noopener noreferrer">KeelCore-750M-Professional</a> (its `onnx/` folder). -->
 
 The ONNX graphs use a cached cross-attention interface (inputs and outputs are listed in `onnx/int8/quantization_info.json`). A reference runner for onnxruntime-web, including LoRA adapter loading, is in the <a href="https://github.com/saravanan-a-r/KeelCore/tree/main/chrome_extension" target="_blank" rel="noopener noreferrer">GitHub repository</a>.
 
@@ -132,7 +132,10 @@ Training state (optimizer moments, RNG state, training logs) is not published.
 
 ### Adapters
 
-KeelCore is one base with many adapters. The base is downloaded once; each adapter is a small separate download that is fitted to this exact base, and an adapter only works with the base it was trained on. The vocabulary reserves 64 command-line task tokens, 36 spare tokens, and mode, style and marker tokens, so a new adapter needs no embedding resize and no change to the base. These text-rewriting adapters are released, each in its own repository:
+KeelCore is one base with many adapters. The base is downloaded once; each adapter is a small separate download that is fitted to this exact base, and an adapter only works with the base it was trained on. The vocabulary reserves 64 command-line task tokens, 36 spare tokens, and mode, style and marker tokens, so a new adapter needs no embedding resize and no change to the base. Adapters for different use cases are in progress.
+
+<!-- ADAPTERS (restore when the adapters are released): replace the sentence above with the following.
+These text-rewriting adapters are released, each in its own repository:
 
 | Adapter | What it does |
 |---|---|
@@ -143,6 +146,7 @@ KeelCore is one base with many adapters. The base is downloaded once; each adapt
 | <a href="https://huggingface.co/KeelCore/KeelCore-750M-Elaborate" target="_blank" rel="noopener noreferrer">KeelCore-750M-Elaborate</a> | Rewrites short, plain text into fuller, more detailed writing |
 
 More adapters, for different use cases, are in progress and will be listed here.
+-->
 
 ## Model Data
 

SHA256SUMS.txt

@@ -9,7 +9,7 @@ f5c8b9b13f888ecd244c7b263f5a106b36a42615d62fa2f598b7958259981b50  ./onnx/int8/en
 09fb8cf0c0370eb4cffe418e8289ffce404a404a46e9f0d66eddd3cdc6a94fed  ./onnx/int8/model.json
 efd89c32b8dac2e87a1df6245b6d04c2aff3b3564308f70c72be2839a5eae68b  ./onnx/int8/quantization_info.json
 98ac32ea00c1ceb866b895c45783d693fecd0388ba70c647feeb58bb1a54ed57  ./onnx/int8/tokenizer.json
-dc21b5cf1343ee35b1a24d42a5f348909cd92603cbd0c9d66149aa220cb724a3  ./README.md
+4e178c9e85f5eb01e63af6781d1abc3a52d86770dd8cf87882b630839b642a86  ./README.md
 f43d87b94c590d88203672e50dfff4bbe82a310a695dfe1728ffb921825b57e9  ./special_tokens_map.json
 e9608233360d9d089327ad668b6719704019b7d0d3c779188d6c5e5600c54f1e  ./spm.model
 718316362ff7eaf6fdd06077a716b23f5c2e453a289878da0648decc71030a18  ./spm.vocab