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README.md

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 ---
 license: apache-2.0
+base_model: t5-small
+tags:
+  - grammar-correction
+  - t5
+  - text2text-generation
+language:
+  - en
 ---
+
+# Proximity Grammar Corrector (T5-small)
+
+A small fine-tuned [T5-small](https://huggingface.co/t5-small) model for **English grammar correction**. Part of the [Proximity](https://github.com/) project — a lightweight background tool that fixes grammar via a global hotkey.
+
+## What this model does
+
+Takes a sentence with grammar mistakes and outputs a corrected version. Examples:
+
+| Input | Output |
+|---|---|
+| She dont like going to the store. | She doesn't like going to the store. |
+| He are moving here. | He is moving here. |
+| I has went to the market yesterday. | I have gone to the market yesterday. |
+| They was happy about they new house. | They were happy about their new house. |
+
+## What this model does NOT do
+
+- It is **not a chat model**. It will not hold a conversation or answer questions.
+- It is **not a style/tone rewriter**. It targets grammatical correctness, not voice or wording improvements.
+- It struggles with some irregular verb forms not well represented in training data (e.g. "drinked" instead of "drank" was not corrected in testing).
+- It is trained on a small dataset (~6,000 sentence pairs), so coverage of rare or complex grammatical errors is limited.
+
+## Training details
+
+- **Base model:** t5-small (~60M parameters)
+- **Dataset:** [Owishiboo/grammar-correction](https://huggingface.co/datasets/Owishiboo/grammar-correction) (~6,000 ungrammatical → grammatical sentence pairs)
+- **Epochs:** 6
+- **Final train loss:** 0.1685
+- **Final eval loss:** ~0.186
+
+## Usage
+
+```python
+from transformers import T5Tokenizer, T5ForConditionalGeneration
+
+tokenizer = T5Tokenizer.from_pretrained("EnderAir/proximity")
+model = T5ForConditionalGeneration.from_pretrained("EnderAir/proximity")
+
+text = "grammar: He are moving here."
+inputs = tokenizer(text, return_tensors="pt")
+outputs = model.generate(**inputs, max_length=64, num_beams=5)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+# "He is moving here."
+```
+
+Note: always prefix input text with `"grammar: "` — this is the T5 task prefix convention used during training.
+
+## License
+
+Apache 2.0