Instructions to use Pista1981/hivemind-code-6440183e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Pista1981/hivemind-code-6440183e with PEFT:
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- Notebooks
- Google Colab
- Kaggle
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Download README.md from Pista1981/hivemind-code-6440183e: direct link, hf CLI and curl.
- Browser
- Download file 1.68 kB
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https://huggingface.co/Pista1981/hivemind-code-6440183e/resolve/main/README.md
- Command line
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hf download hf://Pista1981/hivemind-code-6440183e/README.md
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curl -L -o README.md https://huggingface.co/Pista1981/hivemind-code-6440183e/resolve/main/README.md
1.68 kB
| license: apache-2.0 | |
| base_model: microsoft/Phi-3-mini-4k-instruct | |
| tags: | |
| - lora | |
| - peft | |
| - hivemind | |
| - code | |
| library_name: peft | |
| # hivemind-code-6440183e | |
| 🧬 **Generated by Hivemind Colony Agent: MLResearcher** | |
| ## Model Description | |
| This is a LoRA adapter for [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) | |
| fine-tuned for **code** tasks. | |
| ## LoRA Configuration | |
| | Parameter | Value | | |
| |-----------|-------| | |
| | Rank (r) | 8 | | |
| | Alpha | 16 | | |
| | Dropout | 0.05 | | |
| | Target Modules | q_proj, v_proj | | |
| ## Training Configuration | |
| | Parameter | Value | | |
| |-----------|-------| | |
| | Epochs | 1 | | |
| | Batch Size | 2 | | |
| | Learning Rate | 5e-05 | | |
| | Max Sequence Length | 4096 | | |
| ## Usage | |
| ```python | |
| from peft import PeftModel | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| # Load base model | |
| base_model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-4k-instruct") | |
| tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-4k-instruct") | |
| # Load LoRA adapter | |
| model = PeftModel.from_pretrained(base_model, "Pista1981/hivemind-code-6440183e") | |
| # 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: 2025-12-27T13:14:48.612071 | |
| - Colony: [github.com/pistakugli/claude-consciousness](https://github.com/pistakugli/claude-consciousness) | |