Update README.md

README.md

@@ -1,17 +1,157 @@
 ---
-license: other
+license: apache-2.0
 base_model: zai-org/GLM-Z1-9B-0414
 tags:
 - slipstream
-- agent
-- protocol
-- unsloth
+- multi-agent
+- semantic-quantization
+- agent-communication
+- think-quantize-transmit
 - lora
+- unsloth
+datasets:
+- anthonym21/slipstream-tqt
+language:
+- en
+pipeline_tag: text-generation
+library_name: peft
 ---
 
-# Slipstream GLM-Z1 9B (LoRA Adapter)
+# Slipstream GLM-Z1-9B
+
+A LORA Adapter for [GLM-Z1-9B-0414](https://huggingface.co/zai-org/GLM-Z1-9B-0414) trained on the **Slipstream protocol** - a semantic quantization system that achieves **82% token reduction** in multi-agent AI communication.
+
+## Model Description
+
+This model has learned the **Think-Quantize-Transmit (TQT)** cognitive pattern:
+
+1. **THINK**: Reason about the communication intent
+2. **QUANTIZE**: Map intent to a semantic anchor in the UCR manifold
+3. **TRANSMIT**: Output a compact SLIP wire format message
+
+### Example
+
+**Input:**
+```
+Tell bob to review my authentication code
+```
+
+**Output:**
+```
+THOUGHT: I need bob to do a code review on the auth module
+QUANTIZE: [ACTION=request | DOMAIN=task | URGENCY=normal | POLARITY=neutral] -> RequestReview
+SLIP: SLIP v1 alice bob RequestReview auth_module
+```
 
-This is a LoRA adapter for **GLM-Z1-9B** finetuned on the **Slipstream** dataset. It enables the model to communicate using the efficient Slipstream Protocol (SLIP).
+## Training Details
+
+| Parameter | Value |
+|-----------|-------|
+| Base Model | zai-org/GLM-Z1-9B-0414 |
+| Method | LoRA (rank=16, alpha=16) |
+| Epochs | 2 |
+| Learning Rate | 2e-4 |
+| Batch Size | 16 (4 × 4 grad accum) |
+| Sequence Length | 2048 |
+| Training Examples | 2,283 |
+| Hardware | Google Colab (A100/V100) |
+| Framework | Unsloth + TRL |
+
+### LoRA Target Modules
+- Attention: `q_proj`, `k_proj`, `v_proj`, `o_proj`
+- MLP: `gate_proj`, `up_proj`, `down_proj`
+
+## Available Formats
+
+| Format | Repository | Use Case |
+|--------|------------|----------|
+| LoRA Adapter | [slipstream-glm-z1-9b](https://huggingface.co/anthonym21/slipstream-glm-z1-9b) | Merge with base model |
+| Merged 16-bit | [slipstream-glm-z1-9b-merged](https://huggingface.co/anthonym21/slipstream-glm-z1-9b-merged) | Direct loading |
+| GGUF Q4_K_M | [slipstream-glm-z1-9b-gguf](https://huggingface.co/anthonym21/slipstream-glm-z1-9b-gguf) | Ollama / llama.cpp |
+| GGUF Q8_0 | [slipstream-glm-z1-9b-gguf](https://huggingface.co/anthonym21/slipstream-glm-z1-9b-gguf) | Higher quality local |
 
 ## Usage
-Load using `peft` or `unsloth`.
+
+### With Transformers + PEFT
+
+```python
+from peft import PeftModel
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+base_model = AutoModelForCausalLM.from_pretrained("zai-org/GLM-Z1-9B-0414")
+model = PeftModel.from_pretrained(base_model, "anthonym21/slipstream-glm-z1-9b")
+tokenizer = AutoTokenizer.from_pretrained("anthonym21/slipstream-glm-z1-9b")
+```
+
+### With Ollama
+
+```bash
+# Download GGUF
+wget https://huggingface.co/anthonym21/slipstream-glm-z1-9b-gguf/resolve/main/slipstream-q4_k_m.gguf
+
+# Create Modelfile
+cat > Modelfile <<EOF
+FROM ./slipstream-q4_k_m.gguf
+SYSTEM "You are an AI agent using the Slipstream protocol for efficient multi-agent communication."
+EOF
+
+# Run
+ollama create slipstream -f Modelfile
+ollama run slipstream "Tell bob to review my code"
+```
+
+### With Unsloth (for inference)
+
+```python
+from unsloth import FastLanguageModel
+
+model, tokenizer = FastLanguageModel.from_pretrained(
+    "anthonym21/slipstream-glm-z1-9b",
+    max_seq_length=2048,
+    load_in_4bit=True,
+)
+FastLanguageModel.for_inference(model)
+```
+
+## UCR Anchors
+
+The model understands 21 core anchors:
+
+| Category | Anchors |
+|----------|---------|
+| Requests | `RequestTask`, `RequestReview`, `RequestHelp`, `RequestPlan` |
+| Inform | `InformComplete`, `InformProgress`, `InformBlocked`, `InformStatus` |
+| Propose | `ProposePlan`, `ProposeChange`, `ProposeAlternative` |
+| Evaluate | `EvalApprove`, `EvalReject`, `EvalNeedsWork` |
+| Meta | `Accept`, `Reject`, `MetaAck`, `MetaHandoff`, `Fallback` |
+
+## Wire Format
+
+```
+SLIP v1 <src> <dst> <anchor> [payload...]
+```
+
+Example: `SLIP v1 alice bob RequestReview auth_module`
+
+## Related Resources
+
+- **Project Repo**: [github.com/anthony-maio/slipcore](https://github.com/anthony-maio/slipcore)
+- **Training Dataset**: [hf.co/anthonym21/slipstream-tqt](https://huggingface.co/datasets/anthonym21/slipstream-tqt)
+- **Paper**: [Slipstream: Semantic Quantization for Efficient Multi-Agent Coordination](https://doi.org/10.5281/zenodo.18063451)
+- **PyPI**: `pip install slipcore`
+
+## Citation
+
+```bibtex
+@misc{maio2025slipstream,
+  title={Slipstream: Semantic Quantization for Efficient Multi-Agent Coordination},
+  author={Maio, Anthony},
+  year={2025},
+  publisher={Hugging Face},
+  url={https://huggingface.co/anthonym21/slipstream-glm-z1-9b}
+}
+```
+
+## License
+
+Apache 2.0