Instructions to use c123ian/phi_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use c123ian/phi_test with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/phi-1_5") model = PeftModel.from_pretrained(base_model, "c123ian/phi_test") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "microsoft/phi-1_5", | |
| "activation_function": "gelu_new", | |
| "architectures": [ | |
| "MixFormerSequentialForCausalLM" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "microsoft/phi-1_5--configuration_mixformer_sequential.MixFormerSequentialConfig", | |
| "AutoModelForCausalLM": "microsoft/phi-1_5--modeling_mixformer_sequential.MixFormerSequentialForCausalLM" | |
| }, | |
| "embd_pdrop": 0.0, | |
| "initializer_range": 0.02, | |
| "layer_norm_epsilon": 1e-05, | |
| "model_type": "mixformer-sequential", | |
| "n_embd": 2048, | |
| "n_head": 32, | |
| "n_inner": null, | |
| "n_layer": 24, | |
| "n_positions": 2048, | |
| "resid_pdrop": 0.0, | |
| "rotary_dim": 32, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.33.0", | |
| "vocab_size": 51200 | |
| } | |