Upload Salesforce_CoDA-v0-Instruct_1.txt with huggingface_hub

Salesforce_CoDA-v0-Instruct_1.txt

@@ -0,0 +1,41 @@
+Traceback (most recent call last):
+  File "/tmp/Salesforce_CoDA-v0-Instruct_1MFuvyv.py", line 15, in <module>
+    model = AutoModel.from_pretrained("Salesforce/CoDA-v0-Instruct", trust_remote_code=True, torch_dtype="auto")
+  File "/tmp/.cache/uv/environments-v2/f5cacc24669b9318/lib/python3.13/site-packages/transformers/models/auto/auto_factory.py", line 597, in from_pretrained
+    return model_class.from_pretrained(
+           ~~~~~~~~~~~~~~~~~~~~~~~~~~~^
+        pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs
+        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+    )
+    ^
+  File "/tmp/.cache/uv/environments-v2/f5cacc24669b9318/lib/python3.13/site-packages/transformers/modeling_utils.py", line 277, in _wrapper
+    return func(*args, **kwargs)
+  File "/tmp/.cache/uv/environments-v2/f5cacc24669b9318/lib/python3.13/site-packages/transformers/modeling_utils.py", line 4974, in from_pretrained
+    model = cls(config, *model_args, **model_kwargs)
+  File "/tmp/.cache/huggingface/modules/transformers_modules/Salesforce/CoDA_hyphen_v0_hyphen_Instruct/89d646aff12a3c17079eadba13bd784e74337b41/modeling_coda.py", line 372, in __init__
+    self.model = CoDAModel(config)
+                 ~~~~~~~~~^^^^^^^^
+  File "/tmp/.cache/huggingface/modules/transformers_modules/Salesforce/CoDA_hyphen_v0_hyphen_Instruct/89d646aff12a3c17079eadba13bd784e74337b41/modeling_coda.py", line 268, in __init__
+    super().__init__(config=config)
+    ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^
+  File "/tmp/.cache/uv/environments-v2/f5cacc24669b9318/lib/python3.13/site-packages/transformers/modeling_utils.py", line 2080, in __init__
+    self.config._attn_implementation_internal = self._check_and_adjust_attn_implementation(
+                                                ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
+        self.config._attn_implementation, is_init_check=True
+        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+    )
+    ^
+  File "/tmp/.cache/uv/environments-v2/f5cacc24669b9318/lib/python3.13/site-packages/transformers/modeling_utils.py", line 2690, in _check_and_adjust_attn_implementation
+    applicable_attn_implementation = self.get_correct_attn_implementation(
+        applicable_attn_implementation, is_init_check
+    )
+  File "/tmp/.cache/uv/environments-v2/f5cacc24669b9318/lib/python3.13/site-packages/transformers/modeling_utils.py", line 2729, in get_correct_attn_implementation
+    raise e
+  File "/tmp/.cache/uv/environments-v2/f5cacc24669b9318/lib/python3.13/site-packages/transformers/modeling_utils.py", line 2726, in get_correct_attn_implementation
+    self._sdpa_can_dispatch(is_init_check)
+    ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^
+  File "/tmp/.cache/uv/environments-v2/f5cacc24669b9318/lib/python3.13/site-packages/transformers/modeling_utils.py", line 2578, in _sdpa_can_dispatch
+    raise ValueError(
+    ...<3 lines>...
+    )
+ValueError: CoDAModel does not support an attention implementation through torch.nn.functional.scaled_dot_product_attention yet. Please request the support for this architecture: https://github.com/huggingface/transformers/issues/28005. If you believe this error is a bug, please open an issue in Transformers GitHub repository and load your model with the argument `attn_implementation="eager"` meanwhile. Example: `model = AutoModel.from_pretrained("openai/whisper-tiny", attn_implementation="eager")`