Update README.md

README.md

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 ---
 license: apache-2.0
+language:
+- en
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- gpt2
+- from-scratch
+- tinystories
+- text-generation
+- causal-lm
 ---
+
+# RecursiveComplete
+
+A small GPT-2-style language model (~18.3M parameters) trained **completely from scratch by an AI**, end to end — the architecture, training code, tokenizer, data prep, and training run were all written and executed by an AI agent with no pre-existing weights or fine-tuning from another model.
+
+This is a **text-completion model**, not an instruction-tuned chatbot. It's good at continuing short prose and simple stories. It is **not** good at answering questions, following instructions, or factual recall.
+
+## Model details
+
+| | |
+|---|---|
+| Type | Decoder-only transformer (GPT-2 style) |
+| Parameters | ~18.3M |
+| Embedding dim (`n_embd`) | 448 |
+| Heads (`n_head`) | 7 |
+| Layers (`n_layer`) | 6 |
+| Context length (`block_size`) | 256 |
+| Vocab size | 8192 |
+| Tokenizer | Byte-level BPE (`<eot>` id = 0) |
+| Dropout | 0.1 |
+| Final train loss | ~1.86 |
+
+## Training data
+
+Trained primarily on **TinyStories** (~90M tokens) with a small amount of Alpaca-style data. The model learned general English sentence structure and simple narrative flow, not world knowledge.
+
+## Intended use
+
+- Story / prose continuation
+- Experimentation and education (a clean, fully-from-scratch small LM)
+
+## Limitations
+
+- Completion only — will not reliably answer questions or follow instructions.
+- No factual reliability; it will confidently make things up.
+- Small context (256 tokens) and small vocab.
+- English only.
+
+## How to use
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+tok = AutoTokenizer.from_pretrained("Gentraxyz/RecursiveComplete")
+model = AutoModelForCausalLM.from_pretrained("Gentraxyz/RecursiveComplete")
+
+prompt = "Once upon a time"
+ids = tok(prompt, return_tensors="pt").input_ids
+out = model.generate(ids, max_new_tokens=100, temperature=0.8, top_k=40, do_sample=True)
+print(tok.decode(out[0]))
+```
+
+## License
+
+Apache 2.0.
+
+## Note
+
+This model was trained entirely by an AI — including writing the model code, the tokenizer, the data pipeline, and running the training. It is shared as a small from-scratch experiment.