Instructions to use kamel-usp/jbcs2025_phi-4-phi4_classification_lora-C4-full_context-r16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kamel-usp/jbcs2025_phi-4-phi4_classification_lora-C4-full_context-r16 with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("microsoft/phi-4") model = PeftModel.from_pretrained(base_model, "kamel-usp/jbcs2025_phi-4-phi4_classification_lora-C4-full_context-r16") - Notebooks
- Google Colab
- Kaggle
Download evaluation_results.csv from kamel-usp/jbcs2025_phi-4-phi4_classification_lora-C4-full_context-r16: direct link, hf CLI and curl.
- Browser
- Download file 1.44 kB
-
https://huggingface.co/kamel-usp/jbcs2025_phi-4-phi4_classification_lora-C4-full_context-r16/resolve/main/evaluation_results.csv
- Command line
-
hf download hf://kamel-usp/jbcs2025_phi-4-phi4_classification_lora-C4-full_context-r16/evaluation_results.csv
-
curl -L -o evaluation_results.csv https://huggingface.co/kamel-usp/jbcs2025_phi-4-phi4_classification_lora-C4-full_context-r16/resolve/main/evaluation_results.csv
1.44 kB
| eval_loss,eval_model_preparation_time,eval_accuracy,eval_RMSE,eval_QWK,eval_HDIV,eval_Macro_F1,eval_Micro_F1,eval_Weighted_F1,eval_TP_0,eval_TN_0,eval_FP_0,eval_FN_0,eval_TP_1,eval_TN_1,eval_FP_1,eval_FN_1,eval_TP_2,eval_TN_2,eval_FP_2,eval_FN_2,eval_TP_3,eval_TN_3,eval_FP_3,eval_FN_3,eval_TP_4,eval_TN_4,eval_FP_4,eval_FN_4,eval_TP_5,eval_TN_5,eval_FP_5,eval_FN_5,eval_runtime,eval_samples_per_second,eval_steps_per_second,epoch,reference,timestamp,id | |
| 3.508249521255493,0.0096,0.2878787878787879,43.90071442781686,-0.032264410781034814,0.015151515151515138,0.095,0.2878787878787879,0.1727272727272727,0,131,0,1,0,132,0,0,0,108,20,4,0,68,0,64,38,10,74,10,0,117,0,15,39.5918,3.334,0.834,-1,validation_before_training,2025-07-06 10:19:06,phi-4-phi4_classification_lora-C4-full_context-r16 | |
| 1.2339941263198853,0.0096,0.44696969696969696,34.289321599553055,0.5432363013698631,0.0,0.3228147862918752,0.44696969696969696,0.4604351174432037,0,131,0,1,0,132,0,0,2,118,10,2,24,60,8,40,22,56,28,26,11,90,27,4,39.5312,3.339,0.835,13.0,validation_after_training,2025-07-06 10:19:06,phi-4-phi4_classification_lora-C4-full_context-r16 | |
| 1.1753787994384766,0.0096,0.4782608695652174,31.20757990421976,0.5983367983367983,0.0,0.28940643739961425,0.4782608695652174,0.49833793115813957,0,137,0,1,0,137,0,1,7,104,25,2,30,54,8,46,25,67,25,21,4,119,14,1,42.0636,3.281,0.832,13.0,test_results,2025-07-06 10:19:06,phi-4-phi4_classification_lora-C4-full_context-r16 | |