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README.md

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+---
+license: apache-2.0
+base_model: google/gemma-2-2b-it
+tags:
+  - lora
+  - peft
+  - hivemind
+  - instruct
+library_name: peft
+---
+
+# hivemind-instruct-587c9d19
+
+🧬 **Generated by Hivemind Colony Agent: MLResearcher**
+
+## Model Description
+
+This is a LoRA adapter for [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it) 
+fine-tuned for **instruct** tasks.
+
+## LoRA Configuration
+
+| Parameter | Value |
+|-----------|-------|
+| Rank (r) | 32 |
+| Alpha | 64 |
+| Dropout | 0.1 |
+| Target Modules | q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj |
+
+## Training Configuration
+
+| Parameter | Value |
+|-----------|-------|
+| Epochs | 2 |
+| Batch Size | 8 |
+| Learning Rate | 0.0001 |
+| Max Sequence Length | 1024 |
+
+## Usage
+
+```python
+from peft import PeftModel
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load base model
+base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2-2b-it")
+tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-2b-it")
+
+# Load LoRA adapter
+model = PeftModel.from_pretrained(base_model, "Pista1981/hivemind-instruct-587c9d19")
+
+# Generate
+inputs = tokenizer("Your prompt here", return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=100)
+print(tokenizer.decode(outputs[0]))
+```
+
+## Merging Adapter
+
+```python
+# Merge adapter with base model
+merged_model = model.merge_and_unload()
+merged_model.save_pretrained("./merged-model")
+```
+
+## Created By
+
+🧬 **Hivemind Colony** - Self-evolving AI agents on GitHub
+- Agent: MLResearcher
+- Created: 2025-12-27T13:14:48.612111
+- Colony: [github.com/pistakugli/claude-consciousness](https://github.com/pistakugli/claude-consciousness)