Update app.py

app.py

@@ -52,6 +52,8 @@ BASE_MODEL_IDS: List[str] = [
     "HuggingFaceTB/SmolLM2-135M",
     "OpenCerebral/Boris-1.3-125M",
     "OpenCerebral/Boris-1.3-75M",
+    "CodeSoft/sorbet-v2-25m",
+    "DALabCommunity/Haidass1.5-143M",
 ]
 
 BASE_MODEL_DISPLAY: Dict[str, str] = {
@@ -61,6 +63,8 @@ BASE_MODEL_DISPLAY: Dict[str, str] = {
     "HuggingFaceTB/SmolLM2-135M": "SmolLM2-135M",
     "OpenCerebral/Boris-1.3-125M": "Boris-1.3-125M",
     "OpenCerebral/Boris-1.3-75M": "Boris-1.3-75M",
+    "CodeSoft/sorbet-v2-25m": "sorbet-v2-25m",
+    "DALabCommunity/Haidass1.5-143M": "Haidass1.5-143M",
 }
 
 MODEL_PARAMS: Dict[str, float] = {
@@ -76,6 +80,8 @@ MODEL_PARAMS: Dict[str, float] = {
     "HuggingFaceTB/SmolLM2-135M": 135.0e6,
     "OpenCerebral/Boris-1.3-125M": 125.0e6,
     "OpenCerebral/Boris-1.3-75M": 75.0e6,
+    "CodeSoft/sorbet-v2-25m": 25.2e6,
+    "DALabCommunity/Haidass1.5-143M": 143.0e6,
 }
 
 FALLBACK_IDS: Dict[str, str] = {}
@@ -158,6 +164,8 @@ GEN_DEFAULTS: Dict[str, dict] = {
     "OpenCerebral/Boris-1.3-75M-Instruct": {"max_new_tokens": 64, "temperature": 0.7, "top_p": 0.9, "repetition_penalty": 1.1, "do_sample": True},
     "OpenCerebral/Boris-1.3-125M": {"max_new_tokens": 64, "temperature": 0.8, "top_p": 0.95, "repetition_penalty": 1.1, "do_sample": True},
     "OpenCerebral/Boris-1.3-75M": {"max_new_tokens": 64, "temperature": 0.8, "top_p": 0.95, "repetition_penalty": 1.1, "do_sample": True},
+    "CodeSoft/sorbet-v2-25m": {"max_new_tokens": 64, "temperature": 0.8, "top_p": 0.95, "repetition_penalty": 1.1, "do_sample": True},
+    "DALabCommunity/Haidass1.5-143M": {"max_new_tokens": 64, "temperature": 0.8, "top_p": 0.95, "repetition_penalty": 1.1, "do_sample": True},
 }
 
 MODEL_CONTEXT: Dict[str, int] = {
@@ -173,6 +181,8 @@ MODEL_CONTEXT: Dict[str, int] = {
     "OpenCerebral/Boris-1.3-75M-Instruct": 2048,
     "OpenCerebral/Boris-1.3-125M": 2048,
     "OpenCerebral/Boris-1.3-75M": 2048,
+    "CodeSoft/sorbet-v2-25m": 4096,
+    "DALabCommunity/Haidass1.5-143M": 4096,
 }