--- library_name: peft base_model: mistralai/Mistral-7B-v0.1 datasets: - ise-uiuc/Magicoder-OSS-Instruct-75K --- # Model Card for Model ID Trained with [Ludwig.ai](https://ludwig.ai) and [Predibase](https://predibase.com)! Given a programming problem and a target language, generate a solution. Try it in [LoRAX](https://github.com/predibase/lorax): ```python from lorax import Client client = Client("http://") problem = "" lang = "" prompt = f""" Below is a programming problem, paired with a language in which the solution should be written. Write a solution in the provided that appropriately solves the programming problem. ### Problem: {problem} ### Language: {lang} ### Solution: """ adapter_id = "tgaddair/mistral-7b-magicoder-lora-r8" resp = client.generate(prompt, max_new_tokens=64, adapter_id=adapter_id) print(resp.generated_text) ``` ## Model Details ### Model Description Ludwig config (v0.9.3): ```yaml model_type: llm input_features: - name: prompt type: text preprocessing: max_sequence_length: null column: prompt output_features: - name: solution type: text preprocessing: max_sequence_length: null column: solution prompt: template: >- Below is a programming problem, paired with a language in which the solution should be written. Write a solution in the provided that appropriately solves the programming problem. ### Problem: {problem} ### Language: {lang} ### Solution: preprocessing: split: type: fixed column: split global_max_sequence_length: 2048 adapter: type: lora generation: max_new_tokens: 64 trainer: type: finetune epochs: 1 optimizer: type: paged_adam batch_size: 1 eval_steps: 100 learning_rate: 0.0002 eval_batch_size: 2 steps_per_checkpoint: 1000 learning_rate_scheduler: decay: cosine warmup_fraction: 0.03 gradient_accumulation_steps: 16 enable_gradient_checkpointing: true base_model: mistralai/Mistral-7B-v0.1 quantization: bits: 4 ```