Instructions to use fals3/bigcode-starcoderbase-unit-test-prompt-tuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use fals3/bigcode-starcoderbase-unit-test-prompt-tuning with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigcode/starcoderbase") model = PeftModel.from_pretrained(base_model, "fals3/bigcode-starcoderbase-unit-test-prompt-tuning") - Notebooks
- Google Colab
- Kaggle
| { | |
| "auto_mapping": null, | |
| "base_model_name_or_path": "bigcode/starcoderbase", | |
| "inference_mode": true, | |
| "num_attention_heads": 48, | |
| "num_layers": 40, | |
| "num_transformer_submodules": 1, | |
| "num_virtual_tokens": 20, | |
| "peft_type": "PROMPT_TUNING", | |
| "prompt_tuning_init": "RANDOM", | |
| "prompt_tuning_init_text": null, | |
| "revision": null, | |
| "task_type": "CAUSAL_LM", | |
| "token_dim": 6144, | |
| "tokenizer_kwargs": null, | |
| "tokenizer_name_or_path": "bigcode/starcoderbase" | |
| } |