Add English version of model card before Turkish

README.md

@@ -20,6 +20,87 @@ base_model: sixfingerdev/kayra-1-exp
 
 # 🧠 Kayra-1-Thinking-Exp
 
+**A thinking Turkish language model — Chain-of-Thought reasoning fine-tune of Kayra-1-exp**
+
+This is an experimental fine-tune of [sixfingerdev/kayra-1-exp](https://huggingface.co/sixfingerdev/kayra-1-exp) (86.4M parameters) on a **chain-of-thought reasoning** dataset. It learns to produce step-by-step reasoning within `<|think|>` tags before generating the final answer.
+
+### Model Details
+
+| Property | Value |
+|----------|-------|
+| **Base Model** | [sixfingerdev/kayra-1-exp](https://huggingface.co/sixfingerdev/kayra-1-exp) |
+| **Parameters** | ~86.4M (106.8M with copied tied embeddings) |
+| **Architecture** | Transformer Decoder (GPT-style), 10 layers, 640 hidden, 10 heads |
+| **Context Length** | 512 tokens |
+| **Vocabulary** | 32,000 BPE tokens |
+| **Training Data** | [kayra-thinking-data](https://huggingface.co/datasets/sixfingerdev/kayra-thinking-data) (4,191 Turkish reasoning examples) |
+| **Version** | Experimental (exp) |
+
+### Training
+
+| Hyperparameter | Value |
+|----------------|-------|
+| Epochs | 5 |
+| Batch Size | 8 (per device) |
+| Learning Rate | 5e-5 |
+| Scheduler | Cosine (20 steps warmup) |
+| Optimizer | AdamW |
+| Precision | FP16 |
+| Train / Eval Split | 95% / 5% (3,981 / 210) |
+| Total Steps | 2,490 |
+
+Eval loss decreased from 2.73 → **2.25** over 5 epochs.
+
+### Dataset
+
+Trained on [kayra-thinking-data](https://huggingface.co/datasets/sixfingerdev/kayra-thinking-data): a curated collection of 4,191 Turkish reasoning examples combining 4 sources — duxx (226), efe (350), Gemma-4 generated (32), and ThinkingData-200K-Turkish (~3,583).
+
+Format:
+```text
+### Soru: <question>
+
+### Yanit: <|think|><step-by-step reasoning></|think|><final answer>
+```
+
+### Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained(
+    "sixfingerdev/kayra-1-thinking-exp",
+    trust_remote_code=True
+)
+tokenizer = AutoTokenizer.from_pretrained("sixfingerdev/kayra-1-thinking-exp")
+
+prompt = "### Soru: Türkiye'nin başkenti neresidir?\n\n### Yanit: <|think|>"
+inputs = tokenizer(prompt, return_tensors="pt")
+
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=120,
+    do_sample=True,
+    temperature=0.3,
+    top_k=40,
+    repetition_penalty=1.2,
+    pad_token_id=tokenizer.pad_token_id,
+)
+```
+
+Recommended generation parameters: `temperature=0.3`, `top_k=40`, `repetition_penalty=1.2`, `max_new_tokens=100-150`.
+
+### Known Limitations
+
+1. **Model capacity**: 86M parameters is too small for reliable complex reasoning. The model learns the *format* of thinking but struggles with *correct logical inference*.
+2. **Function-call contamination**: The ThinkingData-200K source contains tool/API call examples. The model may occasionally generate function-call syntax (`get_name_by_id`, `tool_call`).
+3. **Repetition**: Like most small models, it can enter repetitive loops. Use `repetition_penalty` to mitigate.
+4. **Tokenizer spacing**: BPE subword tokenization can introduce spaces in Turkish words ("soruyor" → "sor uyor", "düşüneyim" → "düşün eyim").
+5. **No factuality guarantee**: This is an experimental model. Do not use in production without verification.
+
+---
+
+# 🧠 Kayra-1-Thinking-Exp (Türkçe)
+
 **Düşünen Türkçe model — Chain-of-Thought reasoning fine-tune of Kayra-1-exp**
 
 Bu model, `sixfingerdev/kayra-1-exp` (86.4M parametre) üzerine **chain-of-thought reasoning** formatında fine-tune edilmiş deneysel bir sürümdür. `<|think|>` etiketleri arasında adım adım muhakeme yapıp ardından nihai cevabı üretmeyi öğrenir.