Instructions to use shivam14245/phi3-mini-sensitive-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shivam14245/phi3-mini-sensitive-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("/home/shivam-karlspace/Documents/API Assignment/ml/models/phi3-mini-base") model = PeftModel.from_pretrained(base_model, "shivam14245/phi3-mini-sensitive-lora") - Transformers
How to use shivam14245/phi3-mini-sensitive-lora with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shivam14245/phi3-mini-sensitive-lora")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("shivam14245/phi3-mini-sensitive-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|endoftext|>", | |
| "is_local": true, | |
| "legacy": false, | |
| "local_files_only": false, | |
| "model_max_length": 4096, | |
| "pad_token": "<|endoftext|>", | |
| "padding_side": "left", | |
| "sp_model_kwargs": {}, | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": "<unk>", | |
| "use_default_system_prompt": false | |
| } | |