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I tried to quantize phi-3-vision with AutoFP8, but it didn't work and I got some errors in the process.:
Quantizing weights: 100%|██████████| 726/726 [00:00<00:00, 7888.09it/s]
Calibrating activation scales: 100%|██████████| 512/512 [02:33<00:00, 3.33it/s]
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
Cell In[1], line 21
19 # Load the model, quantize, and save checkpoint
20 model = AutoFP8ForCausalLM.from_pretrained(pretrained_model_dir, quantize_config)
---> 21 model.quantize(examples)
22 model.save_quantized(quantized_model_dir)
File [~/AutoFP8/auto_fp8/modeling.py:126](http://slnxiageneds02.marc.fr.ssg:8888/lab/tree/AutoFP8/auto_fp8/modeling.py#line=125), in AutoFP8ForCausalLM.quantize(self, calibration_tokens)
123 return calibration_tokens.input_ids
124 return calibration_tokens
--> 126 quantize_activations(
127 self.model,
128 self.quantize_config,
129 _prepare_calibration_data(calibration_tokens),
130 )
File [~/AutoFP8/auto_fp8/quantize.py:309](http://slnxiageneds02.marc.fr.ssg:8888/lab/tree/AutoFP8/auto_fp8/quantize.py#line=308), in quantize_activations(model, quantize_config, calibration_tokens)
307 for k_proj_name, v_proj_name in kv_proj_pairs:
308 parent_module_name = ".".join(k_proj_name.split(".")[:-1])
--> 309 assert parent_module_name == ".".join(v_proj_name.split(".")[:-1])
310 parent_module = dict(model.named_modules())[parent_module_name]
312 k_proj = dict(model.named_modules())[k_proj_name]
AssertionError:
Is there some specific setting for Vision models or is it not supported yet ?
Thanks in advance.
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