update code

results/Chronos_small/config.json

@@ -2,5 +2,6 @@
     "model": "Chronos_small",
     "model_type": "pretrained",
     "model_dtype": "float32",
-    "model_link": "https://huggingface.co/amazon/chronos-t5-small"
+    "model_link": "https://huggingface.co/amazon/chronos-t5-small",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/chronos.ipynb"
 }

results/Moirai_base/config.json

@@ -2,5 +2,6 @@
     "model": "Moirai_base",
     "model_type": "pretrained",
     "model_dtype": "float32",
-    "model_link": "https://huggingface.co/Salesforce/moirai-1.1-R-base"
+    "model_link": "https://huggingface.co/Salesforce/moirai-1.1-R-base",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/moirai.ipynb"
 }

results/Moirai_large/config.json

@@ -2,5 +2,6 @@
     "model": "Moirai_large",
     "model_type": "pretrained",
     "model_dtype": "float32",
-    "model_link": "https://huggingface.co/Salesforce/moirai-1.1-R-large"
+    "model_link": "https://huggingface.co/Salesforce/moirai-1.1-R-large",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/moirai.ipynb"
 }

results/Moirai_small/config.json

@@ -2,5 +2,6 @@
     "model": "Moirai_small",
     "model_type": "pretrained",
     "model_dtype": "float32",
-    "model_link": "https://huggingface.co/Salesforce/moirai-1.1-R-large"
+    "model_link": "https://huggingface.co/Salesforce/moirai-1.1-R-large",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/moirai.ipynb"
 }

results/TTM-R2/config.json

@@ -2,5 +2,6 @@
     "model": "TTM-R2",
     "model_type": "fine-tuned",
     "model_dtype": "float32",
-    "model_link": "https://huggingface.co/ibm-granite/granite-timeseries-ttm-r2"
+    "model_link": "https://huggingface.co/ibm-granite/granite-timeseries-ttm-r2",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/ttm.ipynb"
 }

results/chronos_base/config.json

@@ -2,5 +2,6 @@
     "model": "Chronos_base",
     "model_type": "pretrained",
     "model_dtype": "float32",
-    "model_link": "https://huggingface.co/amazon/chronos-t5-base"
+    "model_link": "https://huggingface.co/amazon/chronos-t5-base",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/chronos.ipynb"
 }

results/chronos_bolt_base/config.json

@@ -2,5 +2,6 @@
     "model": "chronos_bolt_base",
     "model_type": "pretrained",
     "model_dtype": "float32",
-    "model_link": "https://huggingface.co/amazon/chronos-bolt-base"
+    "model_link": "https://huggingface.co/amazon/chronos-bolt-base",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/chronos.ipynb"
 }

results/chronos_bolt_small/config.json

@@ -2,5 +2,6 @@
     "model": "chronos_bolt_small",
     "model_type": "pretrained",
     "model_dtype": "float32",
-    "model_link": "https://huggingface.co/amazon/chronos-bolt-small"
+    "model_link": "https://huggingface.co/amazon/chronos-bolt-small",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/chronos.ipynb"
 }

results/chronos_large/config.json

@@ -2,5 +2,6 @@
     "model": "Chronos_large",
     "model_type": "pretrained",
     "model_dtype": "float32",
-    "model_link": "https://huggingface.co/amazon/chronos-t5-large"
+    "model_link": "https://huggingface.co/amazon/chronos-t5-large",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/chronos.ipynb"
 }

results/timesfm_2_0_500m/config.json

@@ -2,5 +2,6 @@
     "model": "timesfm_2_0_500m",
     "model_type": "pretrained",
     "model_dtype": "float32",
-    "model_link": "https://huggingface.co/google/timesfm-2.0-500m-jax"
+    "model_link": "https://huggingface.co/google/timesfm-2.0-500m-jax",
+    "code_link": "https://github.com/SalesforceAIResearch/gift-eval/blob/main/notebooks/timesfm.ipynb"
 }

src/display/formatting.py

@@ -1,9 +1,17 @@
-def model_hyperlink(link, model_name):
-    if link == "":
+def model_hyperlink(model_link, code_link, model_name):
+    if model_link == "":
         return model_name
         # return f'<a target="_blank">{model_name}</a>'
         # return f'<a target="_blank" href="{link}" rel="noopener noreferrer">{model_name}</a>'
-    return f'<a target="_blank" href="{link}" style="color: var(--link-text-color); text-decoration: underline;text-decoration-style: dotted;">{model_name}</a>'
+    else:
+        model_url = f'<a target="_blank" href="{model_link}" style="color: var(--link-text-color); text-decoration: underline;text-decoration-style: dotted;">{model_name}</a>'
+        if code_link == "":
+            return model_url
+        else:
+            code_url = f'<a target="_blank" href="{code_link}" style="color: var(--link-text-color); text-decoration: underline;text-decoration-style: dotted;">code</a>'
+            return f"{model_url} ({code_url})"
+    # return f'<a target="_blank" href="{link}" style="color: var(--link-text-color); text-decoration: underline;text-decoration-style: dotted;">{model_name}</a> | ' \
+    #         f'<a target="_blank" href="https://www.google.com" style="color: var(--link-text-color); text-decoration: underline;text-decoration-style: dotted;">{model_name}_link2</a>'
 
 
 def make_clickable_model(model_name):

src/leaderboard/read_evals.py

@@ -19,6 +19,7 @@ class ModelConfig:
     model: str
     model_link: str = ""
     model_type: ModelType = ModelType.Unknown
+    code_link: str = ""
     precision: Precision = Precision.Unknown
     license: str = "?"
     likes: int = 0
@@ -37,13 +38,14 @@ class ModelConfig:
         model_type = ModelType.from_str(data.get("model_type", ""))
         model = data.get("model", "")
         model_link = data.get("model_link", "")
-        return cls(model=model, model_link=model_link, model_type=model_type, precision=precision)
+        code_link = data.get("code_link", "")
+        return cls(model=model, model_link=model_link, model_type=model_type, code_link=code_link, precision=precision)
 
     def to_dict(self):
         """Converts the model info to a dict compatible with our dataframe display"""
         data_dict = {
             ModelInfoColumn.model.name: self.model,
-            'model_w_link': model_hyperlink(self.model_link, self.model),
+            'model_w_link': model_hyperlink(self.model_link, self.code_link, self.model),
             ModelInfoColumn.precision.name: self.precision.value.name,
             ModelInfoColumn.model_type.name: self.model_type.value.name,
             ModelInfoColumn.model_type_symbol.name: self.model_type.value.symbol,
@@ -220,6 +222,7 @@ def get_model_info(results_path: str, requests_path: str) -> list[ModelConfig]:
     for model_result_filepath in model_result_filepaths:
         # Creation of result
         model_info = ModelConfig.init_from_json_file(model_result_filepath)
+        print(model_result_filepath)
         # eval_result.update_with_request_file(requests_path)
 
         # Store results of same eval together