Detailed Problem Summary
Context:
- Environment: Google Colab (Pro Version using a V100) for training.
- Tool: Utilizing Hugging Face AutoTrain for fine-tuning a language model.
Sequence of Events:
- Initial Training:
- Successfully trained a model using AutoTrain.
- Process seemingly completed without errors, resulting in several output files.
- Missing
config.json
:
- Despite successful training, noticed that the
config.json
file was not generated. - Without
config.json
, the trained model cannot be loaded for inference or further training.
- Manual Configuration:
- Created a
config.json
manually based on a the ‘base model’ used for fine-tuning (NousResearch/Llama-2-7b-chat-hf) plus additional training and adapter parameters derived from the fine-tuned model’s files AutoTrain uploads to the HF repository. - Uploaded this
config.json
to the Hugging Face repository where the model resides.
- Upload to Repository:
- Uploaded all relevant files, including
pytorch_model.bin
,adapter_config.json
,adapter_model.bin
, and others, to a Hugging Face repository namedKabatubare/meta_douglas_2
.
- Model Loading Error:
- Attempted to load the model and encountered the following error:
vbnetCopy code
OSError: Kabatubare/meta_douglas_2 does not appear to have a file named pytorch_model.bin, tf_model.h5, model.ckpt, or flax_model.msgpack.
- File Size Anomaly:
- Noticed that the size of the uploaded
pytorch_model.bin
is only 888 Bytes, which is far smaller than what is typical for such files.
Repository File Structure:
adapter_config.json
adapter_model.bin
added_tokens.json
config.json
(manually added)pytorch_model.bin
(888 Bytes, suspected to be incorrect or incomplete)- Tokenizer files (
tokenizer.json
,tokenizer.model
, etc.) - Training parameters (
training_args.bin
,training_params.json
)
Specific Questions for the Hugging Face Community:
- Configuration File: Why is a
config.json
not generated by AutoTrain by default? Is there a specific setting or flag that needs to be enabled to output this file? - File Size Issue:
- What could cause
pytorch_model.bin
to be so small (888 Bytes)? - Could this be a symptom of an incomplete or failed save operation?
- Manual Configuration:
- Are there standard procedures or checks to verify that a manually created
config.json
is accurate? - Are there tools to validate the
config.json
against the actual PyTorch model file?
- Error Resolution:
- How to resolve the
OSError
encountered while loading the model? - Are there specific requirements for the directory structure when loading models from a Hugging Face repository?
- Model Integrity:
- Given the missing
config.json
and the small size ofpytorch_model.bin
, are there steps to verify the integrity of the trained model?