diff --git a/scripts/deployment/bake_emotion_model.py b/scripts/deployment/bake_emotion_model.py index 84a8aa6cf..8ae891e9d 100644 --- a/scripts/deployment/bake_emotion_model.py +++ b/scripts/deployment/bake_emotion_model.py @@ -11,7 +11,7 @@ def main() -> int: - model_id = os.environ.get("EMOTION_MODEL_ID", "0xmnrv/samo") + model_id = os.environ.get("EMOTION_MODEL_ID", "duelker/samo-goemotions-deberta-v3-large") token = os.environ.get("HF_TOKEN") if token and login is not None: @@ -34,4 +34,4 @@ def main() -> int: if __name__ == "__main__": - raise SystemExit(main()) \ No newline at end of file + raise SystemExit(main()) diff --git a/scripts/deployment/patch_config_and_upload.py b/scripts/deployment/patch_config_and_upload.py index 429b3afcb..31b2af6a3 100644 --- a/scripts/deployment/patch_config_and_upload.py +++ b/scripts/deployment/patch_config_and_upload.py @@ -5,7 +5,7 @@ from transformers import AutoConfig from huggingface_hub import HfApi, HfFolder -MODEL_ID = os.getenv("MODEL_ID", "0xmnrv/samo") +MODEL_ID = os.getenv("MODEL_ID", "duelker/samo-goemotions-deberta-v3-large") # Get token from environment or local storage TOKEN = os.getenv("HF_TOKEN") diff --git a/scripts/maintenance/infer_mapping_and_eval.py b/scripts/maintenance/infer_mapping_and_eval.py index 9922c9506..736933a5c 100644 --- a/scripts/maintenance/infer_mapping_and_eval.py +++ b/scripts/maintenance/infer_mapping_and_eval.py @@ -7,7 +7,7 @@ from sklearn.metrics import f1_score, accuracy_score from scipy.optimize import linear_sum_assignment -MODEL_ID = os.getenv("MODEL_ID", "0xmnrv/samo") +MODEL_ID = os.getenv("MODEL_ID", "duelker/samo-goemotions-deberta-v3-large") TOKEN = os.getenv("HF_TOKEN") or os.getenv("HUGGINGFACE_HUB_TOKEN") DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu") BATCH = int(os.getenv("BATCH_SIZE", "32")) diff --git a/scripts/maintenance/metrics_test.py b/scripts/maintenance/metrics_test.py index 74a5624f9..8920285d4 100644 --- a/scripts/maintenance/metrics_test.py +++ b/scripts/maintenance/metrics_test.py @@ -9,7 +9,7 @@ from transformers import AutoTokenizer, AutoModelForSequenceClassification from sklearn.metrics import f1_score, accuracy_score -MODEL_ID = os.getenv("MODEL_ID", "0xmnrv/samo") +MODEL_ID = os.getenv("MODEL_ID", "duelker/samo-goemotions-deberta-v3-large") TOKEN = os.getenv("HF_TOKEN") or os.getenv("HUGGINGFACE_HUB_TOKEN") DEVICE = "cuda" if torch.cuda.is_available() else "cpu" BATCH = int(os.getenv("BATCH_SIZE", "32")) diff --git a/scripts/testing/hf_serverless_smoke.py b/scripts/testing/hf_serverless_smoke.py index e776c8dba..ab4b9916d 100644 --- a/scripts/testing/hf_serverless_smoke.py +++ b/scripts/testing/hf_serverless_smoke.py @@ -7,7 +7,7 @@ import requests -HF_REPO = os.getenv("HF_REPO", "0xmnrv/samo") +HF_REPO = os.getenv("HF_REPO", "duelker/samo-goemotions-deberta-v3-large") HF_TOKEN = os.getenv("HF_TOKEN") or os.getenv("HUGGINGFACE_TOKEN") API_URL = f"https://api-inference.huggingface.co/models/{HF_REPO}" diff --git a/src/unified_ai_api.py b/src/unified_ai_api.py index d39ec4e6c..d2bab6714 100644 --- a/src/unified_ai_api.py +++ b/src/unified_ai_api.py @@ -402,7 +402,7 @@ async def lifespan(_: FastAPI) -> AsyncGenerator[None, None]: from src.models.emotion_detection.hf_loader import ( load_emotion_model_multi_source ) - hf_model_id = os.getenv("EMOTION_MODEL_ID", "0xmnrv/samo") + hf_model_id = os.getenv("EMOTION_MODEL_ID", "duelker/samo-goemotions-deberta-v3-large") hf_token = os.getenv("HF_TOKEN") local_dir = os.getenv("EMOTION_MODEL_LOCAL_DIR") archive_url = os.getenv("EMOTION_MODEL_ARCHIVE_URL") diff --git a/website/comprehensive-demo.html b/website/comprehensive-demo.html index 229d37d36..56c8f1188 100644 --- a/website/comprehensive-demo.html +++ b/website/comprehensive-demo.html @@ -3,48 +3,34 @@ - SAMO Emotion Detection API - SAMO Deep Learning - - - - - - + Comprehensive SAMO-DL Demo - All Core Features + - - - - - - + + + + + + + + + + + + - + -