Datasets:

---

Fascetta

/

libero_10_baseline

like 0

Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
alora_invocation_tokens: null
alpha_pattern: struct<>
arrow_config: null
auto_mapping: struct<base_model_class: string, parent_library: string>
base_model_name_or_path: null
bias: string
corda_config: null
ensure_weight_tying: bool
eva_config: null
exclude_modules: null
fan_in_fan_out: bool
inference_mode: bool
init_lora_weights: string
layer_replication: null
layers_pattern: null
layers_to_transform: null
loftq_config: struct<>
lora_alpha: int64
lora_bias: bool
lora_dropout: double
megatron_config: null
megatron_core: string
modules_to_save: null
peft_type: string
peft_version: string
qalora_group_size: int64
r: int64
rank_pattern: struct<>
revision: null
target_modules: list<item: string>
target_parameters: null
task_type: null
trainable_token_indices: null
use_dora: bool
use_qalora: bool
use_rslora: bool
vs
norm_stats: struct<state: struct<mean: list<item: double>, std: list<item: double>, q01: list<item: double>, q99: list<item: double>>, actions: struct<mean: list<item: double>, std: list<item: double>, q01: list<item: double>, q99: list<item: double>>>
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 243, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3608, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2368, in _head
                  return next(iter(self.iter(batch_size=n)))
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2573, in iter
                  for key, example in iterator:
                                      ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2060, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2082, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 604, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/table.pxi", line 5039, in pyarrow.lib.Table.from_batches
                File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              alora_invocation_tokens: null
              alpha_pattern: struct<>
              arrow_config: null
              auto_mapping: struct<base_model_class: string, parent_library: string>
              base_model_name_or_path: null
              bias: string
              corda_config: null
              ensure_weight_tying: bool
              eva_config: null
              exclude_modules: null
              fan_in_fan_out: bool
              inference_mode: bool
              init_lora_weights: string
              layer_replication: null
              layers_pattern: null
              layers_to_transform: null
              loftq_config: struct<>
              lora_alpha: int64
              lora_bias: bool
              lora_dropout: double
              megatron_config: null
              megatron_core: string
              modules_to_save: null
              peft_type: string
              peft_version: string
              qalora_group_size: int64
              r: int64
              rank_pattern: struct<>
              revision: null
              target_modules: list<item: string>
              target_parameters: null
              task_type: null
              trainable_token_indices: null
              use_dora: bool
              use_qalora: bool
              use_rslora: bool
              vs
              norm_stats: struct<state: struct<mean: list<item: double>, std: list<item: double>, q01: list<item: double>, q99: list<item: double>>, actions: struct<mean: list<item: double>, std: list<item: double>, q01: list<item: double>, q99: list<item: double>>>