| --- |
| license: apache-2.0 |
| language: |
| - en |
| pipeline_tag: text-generation |
| tags: |
| - code |
| - code-generation |
| - parrot-coder |
| - inserloft |
| --- |
|  |
|
|
| # Parrot Coder 🦜 |
|
|
| **Parrot Coder** is a highly efficient, 200M parameter language model optimized for rapid code autocompletion and code generation tasks. Developed by Inserloft Research. |
|
|
| This repository contains the **merged base model + LoRA adapters** in `.safetensors` format, ready for direct inference using `transformers`. |
|
|
| ## Usage |
|
|
| ```python |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| |
| model_id = "InserloftResearch/Parrot-Coder" |
| tokenizer = AutoTokenizer.from_pretrained(model_id) |
| model = AutoModelForCausalLM.from_pretrained(model_id) |
| |
| prompt = "def fibonacci(n):" |
| inputs = tokenizer(prompt, return_tensors="pt") |
| outputs = model.generate(**inputs, max_new_tokens=50) |
| print(tokenizer.decode(outputs[0], skip_special_tokens=True)) |
| ``` |
|
|
| For GGUF versions, visit our [Ollama Registry](https://ollama.com/Inserloft/ParrotCode). |
|
|
