| |
| import os |
| from distilabel.pipeline import Pipeline |
| from distilabel.steps import KeepColumns |
| from distilabel.steps.tasks import MagpieGenerator |
| from distilabel.llms import InferenceEndpointsLLM |
|
|
| SYSTEM_PROMPT = "None" |
|
|
| with Pipeline(name="sft") as pipeline: |
| magpie = MagpieGenerator( |
| llm=InferenceEndpointsLLM.from_dict( |
| {'use_magpie_template': False, 'magpie_pre_query_template': None, 'generation_kwargs': {}, 'use_offline_batch_generation': False, 'offline_batch_generation_block_until_done': None, 'jobs_ids': None, 'model_id': 'meta-llama/Llama-3.1-8B-Instruct', 'endpoint_name': None, 'endpoint_namespace': None, 'base_url': None, 'tokenizer_id': 'meta-llama/Llama-3.1-8B-Instruct', 'model_display_name': None, 'structured_output': None, 'type_info': {'module': 'distilabel.models.llms.huggingface.inference_endpoints', 'name': 'InferenceEndpointsLLM'}} |
| ), |
| n_turns=1, |
| num_rows=10, |
| batch_size=1, |
| system_prompt=SYSTEM_PROMPT, |
| output_mappings={'instruction': 'prompt', 'response': 'completion'}, |
| ) |
| keep_columns = KeepColumns( |
| columns=['prompt', 'completion'] + ["model_name"], |
| ) |
| magpie.connect(keep_columns) |
|
|
| if __name__ == "__main__": |
| distiset = pipeline.run() |
