Upload 0xSero_GLM-4.7-REAP-50-W4A16_0.txt with huggingface_hub

0xSero_GLM-4.7-REAP-50-W4A16_0.txt

@@ -0,0 +1,53 @@
+```CODE: 
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+pipe = pipeline("text-generation", model="0xSero/GLM-4.7-REAP-50-W4A16")
+messages = [
+    {"role": "user", "content": "Who are you?"},
+]
+pipe(messages)
+```
+
+ERROR: 
+Traceback (most recent call last):
+  File "/tmp/0xSero_GLM-4.7-REAP-50-W4A16_0K0sWmy.py", line 26, in <module>
+    pipe = pipeline("text-generation", model="0xSero/GLM-4.7-REAP-50-W4A16")
+  File "/tmp/.cache/uv/environments-v2/57fea2d03e820408/lib/python3.13/site-packages/transformers/pipelines/__init__.py", line 1027, in pipeline
+    framework, model = infer_framework_load_model(
+                       ~~~~~~~~~~~~~~~~~~~~~~~~~~^
+        adapter_path if adapter_path is not None else model,
+        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+    ...<5 lines>...
+        **model_kwargs,
+        ^^^^^^^^^^^^^^^
+    )
+    ^
+  File "/tmp/.cache/uv/environments-v2/57fea2d03e820408/lib/python3.13/site-packages/transformers/pipelines/base.py", line 293, in infer_framework_load_model
+    model = model_class.from_pretrained(model, **kwargs)
+  File "/tmp/.cache/uv/environments-v2/57fea2d03e820408/lib/python3.13/site-packages/transformers/models/auto/auto_factory.py", line 604, 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-v2/57fea2d03e820408/lib/python3.13/site-packages/transformers/modeling_utils.py", line 277, in _wrapper
+    return func(*args, **kwargs)
+  File "/tmp/.cache/uv/environments-v2/57fea2d03e820408/lib/python3.13/site-packages/transformers/modeling_utils.py", line 4881, in from_pretrained
+    hf_quantizer, config, dtype, device_map = get_hf_quantizer(
+                                              ~~~~~~~~~~~~~~~~^
+        config, quantization_config, dtype, from_tf, from_flax, device_map, weights_only, user_agent
+        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+    )
+    ^
+  File "/tmp/.cache/uv/environments-v2/57fea2d03e820408/lib/python3.13/site-packages/transformers/quantizers/auto.py", line 311, in get_hf_quantizer
+    hf_quantizer = AutoHfQuantizer.from_config(
+        config.quantization_config,
+        pre_quantized=pre_quantized,
+    )
+  File "/tmp/.cache/uv/environments-v2/57fea2d03e820408/lib/python3.13/site-packages/transformers/quantizers/auto.py", line 185, in from_config
+    return target_cls(quantization_config, **kwargs)
+  File "/tmp/.cache/uv/environments-v2/57fea2d03e820408/lib/python3.13/site-packages/transformers/quantizers/quantizer_gptq.py", line 49, in __init__
+    raise ImportError("Loading a GPTQ quantized model requires optimum (`pip install optimum`)")
+ImportError: Loading a GPTQ quantized model requires optimum (`pip install optimum`)