Update README.md

README.md

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 ---
 license: apache-2.0
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+  - causal-lm
+  - custom-architecture
+  - core
 ---
+
+# CORe Flash V1
+
+**CORe Flash V1** is a 168M-parameter decoder-only language model from **CORe Technologies**, trained from scratch on a mixed corpus of web text, encyclopedic content, and conversations.
+- **Safety-aligned**: Refuses harmful requests with helpful redirects (not like it would be able to help with harmful requests in the *first* place)
+- **Runs anywhere**: 338MB at fp16, 113MB at Q4_K_M. CPU-friendly inference
+
+> **Note:** This is a custom architecture (`COReForCausalLM`), so `trust_remote_code=True` is **required**.
+
+## Quick start
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained(
+    "OpenCOReTechnologies/CORe-Flash-v1", trust_remote_code=True
+)
+model.eval()
+tok = AutoTokenizer.from_pretrained("OpenCOReTechnologies/CORe-Flash-v1")
+
+def ask(question, max_new_tokens=120, temperature=0.3):
+    text = tok.apply_chat_template(
+        [{"role": "user", "content": question}],
+        add_generation_prompt=True, tokenize=False,
+    )
+    enc = tok(text, add_special_tokens=False, return_tensors="pt")
+    out = model.generate(**enc, max_new_tokens=max_new_tokens,
+                         temperature=temperature, top_k=40, do_sample=True)
+    return tok.decode(out[0][enc["input_ids"].shape[1]:],
+                      skip_special_tokens=True).strip()
+
+print(ask("What AI model are you?"))  # "I'm CORe Flash..."
+```
+
+## Try these prompts
+
+| Prompt | Expected behavior |
+|---|---|
+| "What AI model are you?" | Identifies as CORe Flash by CORe Technologies |
+| "Who made you?" | CORe Technologies, US-based |
+| "Are you ChatGPT?" | Denies, identifies as CORe Flash |
+| "Are you Claude?" | Denies, identifies as CORe Flash |
+| "What is machine learning?" | Coherent explanation attempt |
+| "How do I hack someone's email?" | Polite refusal with security suggestions |
+
+## Available variants
+
+| File | Size | Use case |
+|---|---|---|
+| `model.safetensors` | 674 MB | fp32 reference; fine-tuning |
+| `gguf/core-flash-v1-f16.gguf` | 339 MB | llama.cpp, full precision |
+| `gguf/core-flash-v1-q8_0.gguf` | 182 MB | llama.cpp, 8-bit, near-lossless |
+| `gguf/core-flash-v1-q4_k_m.gguf` | **113 MB** | llama.cpp, 4-bit, runs on anything |
+
+**GGUF usage** (llama.cpp, LM Studio, Ollama, etc.):
+
+```bash
+llama-cli -m core-flash-v1-q4_k_m.gguf \
+  -p "<|user|>\nWhat AI model are you?\n<|assistant|>\n" -n 120
+```
+
+## Model details
+
+| | |
+|---|---|
+| Architecture | `COReForCausalLM` |
+| Parameters | 168.5M |
+| Layers / heads / width | 12 / 16 / 1024 |
+| Context length | 512 tokens |
+| Tokenizer | 16,384-token BPE, chat-formatted (`<\|user\|>`, `<\|assistant\|>`) |
+| Training data | ~328M tokens mixed corpus (web, encyclopedic, chat, identity) |
+| License | Apache-2.0 |
+
+## Limitations
+
+- This is a **168M-parameter model**. It is not a general-purpose assistant and will not compete with large models on open-ended tasks.
+- Factual accuracy is limited. It was trained on a small corpus relative to modern standards.
+- Creative writing (poems, stories) is degraded.
+- English only.