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JSONDecodeError Traceback (most recent call last)
Cell In[9], line 6
3 path = "/opt/GPT/MODEL/aya-101/"
5 tokenizer = AutoTokenizer.from_pretrained(path)
----> 6 model = AutoModelForSeq2SeqLM.from_pretrained(path)

File /opt/anaconda3/envs/gpt/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:566, in _BaseAutoModelClass.from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
564 elif type(config) in cls._model_mapping.keys():
565 model_class = _get_model_class(config, cls._model_mapping)
--> 566 return model_class.from_pretrained(
567 pretrained_model_name_or_path, *model_args, config=config, **hub_kwargs, **kwargs
568 )
569 raise ValueError(
570 f"Unrecognized configuration class {config.class} for this kind of AutoModel: {cls.name}.\n"
571 f"Model type should be one of {', '.join(c.name for c in cls._model_mapping.keys())}."
572 )

File /opt/anaconda3/envs/gpt/lib/python3.10/site-packages/transformers/modeling_utils.py:3485, in PreTrainedModel.from_pretrained(cls, pretrained_model_name_or_path, config, cache_dir, ignore_mismatched_sizes, force_download, local_files_only, token, revision, use_safetensors, *model_args, **kwargs)
3482 # We'll need to download and cache each checkpoint shard if the checkpoint is sharded.
3483 if is_sharded:
3484 # rsolved_archive_file becomes a list of files that point to the different checkpoint shards in this case.
-> 3485 resolved_archive_file, sharded_metadata = get_checkpoint_shard_files(
3486 pretrained_model_name_or_path,
3487 resolved_archive_file,
3488 cache_dir=cache_dir,
3489 force_download=force_download,
3490 proxies=proxies,
3491 resume_download=resume_download,
3492 local_files_only=local_files_only,
3493 token=token,
3494 user_agent=user_agent,
3495 revision=revision,
3496 subfolder=subfolder,
3497 _commit_hash=commit_hash,
3498 )
3500 if (
3501 is_safetensors_available()
3502 and isinstance(resolved_archive_file, str)
3503 and resolved_archive_file.endswith(".safetensors")
3504 ):
3505 with safe_open(resolved_archive_file, framework="pt") as f:

File /opt/anaconda3/envs/gpt/lib/python3.10/site-packages/transformers/utils/hub.py:1002, in get_checkpoint_shard_files(pretrained_model_name_or_path, index_filename, cache_dir, force_download, proxies, resume_download, local_files_only, token, user_agent, revision, subfolder, _commit_hash, **deprecated_kwargs)
999 raise ValueError(f"Can't find a checkpoint index ({index_filename}) in {pretrained_model_name_or_path}.")
1001 with open(index_filename, "r") as f:
-> 1002 index = json.loads(f.read())
1004 shard_filenames = sorted(set(index["weight_map"].values()))
1005 sharded_metadata = index["metadata"]

File /opt/anaconda3/envs/gpt/lib/python3.10/json/init.py:346, in loads(s, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)
341 s = s.decode(detect_encoding(s), 'surrogatepass')
343 if (cls is None and object_hook is None and
344 parse_int is None and parse_float is None and
345 parse_constant is None and object_pairs_hook is None and not kw):
--> 346 return _default_decoder.decode(s)
347 if cls is None:
348 cls = JSONDecoder

File /opt/anaconda3/envs/gpt/lib/python3.10/json/decoder.py:337, in JSONDecoder.decode(self, s, _w)
332 def decode(self, s, _w=WHITESPACE.match):
333 """Return the Python representation of s (a str instance
334 containing a JSON document).
335
336 """
--> 337 obj, end = self.raw_decode(s, idx=_w(s, 0).end())
338 end = _w(s, end).end()
339 if end != len(s):

File /opt/anaconda3/envs/gpt/lib/python3.10/json/decoder.py:355, in JSONDecoder.raw_decode(self, s, idx)
353 obj, end = self.scan_once(s, idx)
354 except StopIteration as err:
--> 355 raise JSONDecodeError("Expecting value", s, err.value) from None
356 return obj, end

JSONDecodeError: Expecting value: line 1 column 1 (char 0)