Upload cyankiwi_GLM-4.7-Flash-AWQ-4bit_0.txt with huggingface_hub

cyankiwi_GLM-4.7-Flash-AWQ-4bit_0.txt

@@ -11,26 +11,49 @@ pipe(messages)
 
 ERROR: 
 Traceback (most recent call last):
-  File "/tmp/.cache/uv/environments-v2/4a272a7d010dadc8/lib/python3.13/site-packages/transformers/models/auto/configuration_auto.py", line 1360, in from_pretrained
-    config_class = CONFIG_MAPPING[config_dict["model_type"]]
-                   ~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "/tmp/.cache/uv/environments-v2/4a272a7d010dadc8/lib/python3.13/site-packages/transformers/models/auto/configuration_auto.py", line 1048, in __getitem__
-    raise KeyError(key)
-KeyError: 'glm4_moe_lite'
-
-During handling of the above exception, another exception occurred:
-
-Traceback (most recent call last):
-  File "/tmp/cyankiwi_GLM-4.7-Flash-AWQ-4bit_0gpVaou.py", line 26, in <module>
+  File "/tmp/cyankiwi_GLM-4.7-Flash-AWQ-4bit_04Cpv3J.py", line 26, in <module>
     pipe = pipeline("text-generation", model="cyankiwi/GLM-4.7-Flash-AWQ-4bit")
-  File "/tmp/.cache/uv/environments-v2/4a272a7d010dadc8/lib/python3.13/site-packages/transformers/pipelines/__init__.py", line 922, in pipeline
-    config = AutoConfig.from_pretrained(
-        model, _from_pipeline=task, code_revision=code_revision, **hub_kwargs, **model_kwargs
+  File "/tmp/.cache/uv/environments-v2/4a272a7d010dadc8/lib/python3.13/site-packages/transformers/pipelines/__init__.py", line 836, in pipeline
+    model = load_model(
+        adapter_path if adapter_path is not None else model,
+    ...<4 lines>...
+        **model_kwargs,
     )
-  File "/tmp/.cache/uv/environments-v2/4a272a7d010dadc8/lib/python3.13/site-packages/transformers/models/auto/configuration_auto.py", line 1362, in from_pretrained
-    raise ValueError(
-    ...<8 lines>...
+  File "/tmp/.cache/uv/environments-v2/4a272a7d010dadc8/lib/python3.13/site-packages/transformers/pipelines/base.py", line 232, in load_model
+    model = model_class.from_pretrained(model, **kwargs)
+  File "/tmp/.cache/uv/environments-v2/4a272a7d010dadc8/lib/python3.13/site-packages/transformers/models/auto/auto_factory.py", line 372, in from_pretrained
+    return model_class.from_pretrained(
+           ~~~~~~~~~~~~~~~~~~~~~~~~~~~^
+        pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs
+        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
     )
-ValueError: The checkpoint you are trying to load has model type `glm4_moe_lite` but Transformers does not recognize this architecture. This could be because of an issue with the checkpoint, or because your version of Transformers is out of date.
-
-You can update Transformers with the command `pip install --upgrade transformers`. If this does not work, and the checkpoint is very new, then there may not be a release version that supports this model yet. In this case, you can get the most up-to-date code by installing Transformers from source with the command `pip install git+https://github.com/huggingface/transformers.git`
+    ^
+  File "/tmp/.cache/uv/environments-v2/4a272a7d010dadc8/lib/python3.13/site-packages/transformers/modeling_utils.py", line 4015, in from_pretrained
+    hf_quantizer, config, device_map = get_hf_quantizer(
+                                       ~~~~~~~~~~~~~~~~^
+        config, quantization_config, device_map, weights_only, user_agent
+        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+    )
+    ^
+  File "/tmp/.cache/uv/environments-v2/4a272a7d010dadc8/lib/python3.13/site-packages/transformers/quantizers/auto.py", line 312, in get_hf_quantizer
+    config.quantization_config = AutoHfQuantizer.merge_quantization_configs(
+                                 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^
+        config.quantization_config, quantization_config
+        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+    )
+    ^
+  File "/tmp/.cache/uv/environments-v2/4a272a7d010dadc8/lib/python3.13/site-packages/transformers/quantizers/auto.py", line 213, in merge_quantization_configs
+    quantization_config = AutoQuantizationConfig.from_dict(quantization_config)
+  File "/tmp/.cache/uv/environments-v2/4a272a7d010dadc8/lib/python3.13/site-packages/transformers/quantizers/auto.py", line 139, in from_dict
+    return target_cls.from_dict(quantization_config_dict)
+           ~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/tmp/.cache/uv/environments-v2/4a272a7d010dadc8/lib/python3.13/site-packages/transformers/utils/quantization_config.py", line 1203, in from_dict
+    return super().from_dict(config_dict, return_unused_kwargs=return_unused_kwargs, **kwargs)
+           ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/tmp/.cache/uv/environments-v2/4a272a7d010dadc8/lib/python3.13/site-packages/transformers/utils/quantization_config.py", line 115, in from_dict
+    config = cls(**config_dict)
+  File "/tmp/.cache/uv/environments-v2/4a272a7d010dadc8/lib/python3.13/site-packages/transformers/utils/quantization_config.py", line 1133, in __init__
+    raise ImportError(
+        "compressed_tensors is not installed and is required for compressed-tensors quantization. Please install it with `pip install compressed-tensors`."
+    )
+ImportError: compressed_tensors is not installed and is required for compressed-tensors quantization. Please install it with `pip install compressed-tensors`.