pipe = pipeline(model_path = '/cpfs/data/user/ken/amd_adp/OpenGVLab/Internvl_Chat_v1-2-Plus_lora', model_name = "Internvl_Chat_v1-2-Plus_lora")
trainable params: 122,880,000 || all params: 34,511,897,600 || trainable%: 0.35605112597459726
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
Traceback (most recent call last):
File "", line 1, in
File "/usr/local/lib/python3.10/site-packages/lmdeploy/api.py", line 94, in pipeline
return pipeline_class(model_path,
File "/usr/local/lib/python3.10/site-packages/lmdeploy/serve/vl_async_engine.py", line 17, in init
super().init(model_path, **kwargs)
File "/usr/local/lib/python3.10/site-packages/lmdeploy/serve/async_engine.py", line 206, in init
self._build_turbomind(model_path=model_path,
File "/usr/local/lib/python3.10/site-packages/lmdeploy/serve/async_engine.py", line 254, in _build_turbomind
self.engine = tm.TurboMind.from_pretrained(
File "/usr/local/lib/python3.10/site-packages/lmdeploy/turbomind/turbomind.py", line 396, in from_pretrained
return cls(model_path=pretrained_model_name_or_path,
File "/usr/local/lib/python3.10/site-packages/lmdeploy/turbomind/turbomind.py", line 170, in init
self.model_comm = self._from_hf(model_source=model_source,
File "/usr/local/lib/python3.10/site-packages/lmdeploy/turbomind/turbomind.py", line 279, in _from_hf
output_model = OUTPUT_MODELS.get(output_format)(
File "/usr/local/lib/python3.10/site-packages/lmdeploy/turbomind/deploy/target_model/fp.py", line 26, in init
super().init(input_model, cfg, to_file, out_dir)
File "/usr/local/lib/python3.10/site-packages/lmdeploy/turbomind/deploy/target_model/base.py", line 156, in init
assert self.cfg.valid
AssertionError
pipe = pipeline(model_path = '/cpfs/data/user/ken/amd_adp/OpenGVLab/Internvl_Chat_v1-2-Plus_lora', model_name = "Internvl_Chat_v1-2-Plus_lora") trainable params: 122,880,000 || all params: 34,511,897,600 || trainable%: 0.35605112597459726 Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained. Traceback (most recent call last): File "", line 1, in
File "/usr/local/lib/python3.10/site-packages/lmdeploy/api.py", line 94, in pipeline
return pipeline_class(model_path,
File "/usr/local/lib/python3.10/site-packages/lmdeploy/serve/vl_async_engine.py", line 17, in init
super().init(model_path, **kwargs)
File "/usr/local/lib/python3.10/site-packages/lmdeploy/serve/async_engine.py", line 206, in init
self._build_turbomind(model_path=model_path,
File "/usr/local/lib/python3.10/site-packages/lmdeploy/serve/async_engine.py", line 254, in _build_turbomind
self.engine = tm.TurboMind.from_pretrained(
File "/usr/local/lib/python3.10/site-packages/lmdeploy/turbomind/turbomind.py", line 396, in from_pretrained
return cls(model_path=pretrained_model_name_or_path,
File "/usr/local/lib/python3.10/site-packages/lmdeploy/turbomind/turbomind.py", line 170, in init
self.model_comm = self._from_hf(model_source=model_source,
File "/usr/local/lib/python3.10/site-packages/lmdeploy/turbomind/turbomind.py", line 279, in _from_hf
output_model = OUTPUT_MODELS.get(output_format)(
File "/usr/local/lib/python3.10/site-packages/lmdeploy/turbomind/deploy/target_model/fp.py", line 26, in init
super().init(input_model, cfg, to_file, out_dir)
File "/usr/local/lib/python3.10/site-packages/lmdeploy/turbomind/deploy/target_model/base.py", line 156, in init
assert self.cfg.valid
AssertionError