Datasets:

cckavin
/

vicuna_weights_13b

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train

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The dataset generation failed because of a cast error

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 2 new columns ({'weight_map', 'metadata'}) and 5 missing columns ({'bos_token_id', 'transformers_version', 'pad_token_id', 'eos_token_id', '_from_model_config'}).

This happened while the json dataset builder was generating data using

hf://datasets/cckavin/vicuna_weights_13b/pytorch_model.bin.index.json (at revision 381591fa0902066b08ffbfccfcf4656056a3996c)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              metadata: struct<total_size: int64>
                child 0, total_size: int64
              weight_map: struct<lm_head.weight: string, model.embed_tokens.weight: string, model.layers.0.input_layernorm.weight: string, model.layers.0.mlp.down_proj.weight: string, model.layers.0.mlp.gate_proj.weight: string, model.layers.0.mlp.up_proj.weight: string, model.layers.0.post_attention_layernorm.weight: string, model.layers.0.self_attn.k_proj.weight: string, model.layers.0.self_attn.o_proj.weight: string, model.layers.0.self_attn.q_proj.weight: string, model.layers.0.self_attn.rotary_emb.inv_freq: string, model.layers.0.self_attn.v_proj.weight: string, model.layers.1.input_layernorm.weight: string, model.layers.1.mlp.down_proj.weight: string, model.layers.1.mlp.gate_proj.weight: string, model.layers.1.mlp.up_proj.weight: string, model.layers.1.post_attention_layernorm.weight: string, model.layers.1.self_attn.k_proj.weight: string, model.layers.1.self_attn.o_proj.weight: string, model.layers.1.self_attn.q_proj.weight: string, model.layers.1.self_attn.rotary_emb.inv_freq: string, model.layers.1.self_attn.v_proj.weight: string, model.layers.10.input_layernorm.weight: string, model.layers.10.mlp.down_proj.weight: string, model.layers.10.mlp.gate_proj.weight: string, model.layers.10.mlp.up_proj.weight: string, model.layers.10.post_attention_layernorm.weight: string, model.layers.10.self_attn.k_proj.weight: string, model.layers.10.self_attn.o_proj.weight: string, model.layers.10.self_attn.q_proj.weight: string, model
              ...
              ght: string
                child 378, model.layers.7.self_attn.o_proj.weight: string
                child 379, model.layers.7.self_attn.q_proj.weight: string
                child 380, model.layers.7.self_attn.rotary_emb.inv_freq: string
                child 381, model.layers.7.self_attn.v_proj.weight: string
                child 382, model.layers.8.input_layernorm.weight: string
                child 383, model.layers.8.mlp.down_proj.weight: string
                child 384, model.layers.8.mlp.gate_proj.weight: string
                child 385, model.layers.8.mlp.up_proj.weight: string
                child 386, model.layers.8.post_attention_layernorm.weight: string
                child 387, model.layers.8.self_attn.k_proj.weight: string
                child 388, model.layers.8.self_attn.o_proj.weight: string
                child 389, model.layers.8.self_attn.q_proj.weight: string
                child 390, model.layers.8.self_attn.rotary_emb.inv_freq: string
                child 391, model.layers.8.self_attn.v_proj.weight: string
                child 392, model.layers.9.input_layernorm.weight: string
                child 393, model.layers.9.mlp.down_proj.weight: string
                child 394, model.layers.9.mlp.gate_proj.weight: string
                child 395, model.layers.9.mlp.up_proj.weight: string
                child 396, model.layers.9.post_attention_layernorm.weight: string
                child 397, model.layers.9.self_attn.k_proj.weight: string
                child 398, model.layers.9.self_attn.o_proj.weight: string
                child 399, model.layers.9.self_attn.q_proj.weight: string
                child 400, model.layers.9.self_attn.rotary_emb.inv_freq: string
                child 401, model.layers.9.self_attn.v_proj.weight: string
                child 402, model.norm.weight: string
              to
              {'_from_model_config': Value(dtype='bool', id=None), 'bos_token_id': Value(dtype='int64', id=None), 'eos_token_id': Value(dtype='int64', id=None), 'pad_token_id': Value(dtype='int64', id=None), 'transformers_version': Value(dtype='string', id=None)}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1321, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 935, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 2 new columns ({'weight_map', 'metadata'}) and 5 missing columns ({'bos_token_id', 'transformers_version', 'pad_token_id', 'eos_token_id', '_from_model_config'}).
              
              This happened while the json dataset builder was generating data using
              
              hf://datasets/cckavin/vicuna_weights_13b/pytorch_model.bin.index.json (at revision 381591fa0902066b08ffbfccfcf4656056a3996c)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

_from_model_config bool	bos_token_id int64	eos_token_id int64	pad_token_id int64	transformers_version string	metadata dict	weight_map dict	bos_token dict	eos_token dict	unk_token dict	add_bos_token bool	add_eos_token bool	clean_up_tokenization_spaces bool	model_max_length float64	pad_token null	sp_model_kwargs dict	tokenizer_class string
true	0	1	0	4.29.0.dev0	null	null	null	null	null	null	null	null	null	null	null	null
null	null	null	null	null	{ "total_size": 26031759360 }	{ "lm_head.weight": "pytorch_model-00003-of-00003.bin", "model.embed_tokens.weight": "pytorch_model-00001-of-00003.bin", "model.layers.0.input_layernorm.weight": "pytorch_model-00001-of-00003.bin", "model.layers.0.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.0.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.0.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.0.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin", "model.layers.0.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.0.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.0.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.0.self_attn.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin", "model.layers.0.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.1.input_layernorm.weight": "pytorch_model-00001-of-00003.bin", "model.layers.1.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.1.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.1.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.1.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin", "model.layers.1.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.1.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.1.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.1.self_attn.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin", "model.layers.1.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.10.input_layernorm.weight": "pytorch_model-00001-of-00003.bin", "model.layers.10.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.10.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.10.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.10.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin", "model.layers.10.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.10.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.10.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.10.self_attn.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin", "model.layers.10.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.11.input_layernorm.weight": "pytorch_model-00001-of-00003.bin", "model.layers.11.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.11.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.11.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.11.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin", "model.layers.11.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.11.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.11.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.11.self_attn.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin", "model.layers.11.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.12.input_layernorm.weight": "pytorch_model-00001-of-00003.bin", "model.layers.12.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.12.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.12.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.12.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin", "model.layers.12.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.12.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.12.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.12.self_attn.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin", "model.layers.12.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.13.input_layernorm.weight": "pytorch_model-00001-of-00003.bin", "model.layers.13.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.13.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.13.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.13.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin", "model.layers.13.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.13.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.13.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.13.self_attn.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin", "model.layers.13.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.14.input_layernorm.weight": 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"model.layers.15.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin", "model.layers.15.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin", "model.layers.15.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.15.self_attn.o_proj.weight": "pytorch_model-00002-of-00003.bin", "model.layers.15.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin", "model.layers.15.self_attn.rotary_emb.inv_freq": "pytorch_model-00002-of-00003.bin", "model.layers.15.self_attn.v_proj.weight": "pytorch_model-00002-of-00003.bin", "model.layers.16.input_layernorm.weight": "pytorch_model-00002-of-00003.bin", "model.layers.16.mlp.down_proj.weight": "pytorch_model-00002-of-00003.bin", "model.layers.16.mlp.gate_proj.weight": "pytorch_model-00002-of-00003.bin", "model.layers.16.mlp.up_proj.weight": "pytorch_model-00002-of-00003.bin", "model.layers.16.post_attention_layernorm.weight": "pytorch_model-00002-of-00003.bin", "model.layers.16.self_attn.k_proj.weight": 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