While following through our tutorials, you might have had questions regarding the details of the requirements and specifications. We have listed out the frequently asked questions and as a separate document. Please refer to the relevant information below:

Format Requirements

General requirements for a model

  • A model should be in safetensors format.
  • The model should NOT be nested inside another directory.
  • Including other arbitrary files (that are not in the list) is totally fine. However, those files will not be downloaded nor used.
RequiredFilenameDescription
YessafetensorsModel weight, e.g. model-00001-of-00002.safetensors
Yesconfig.jsonModel config file that includes the architecture. (Supported Models on Friendli)
Yestokenizer.jsonTokenizer for the model
Notokenizer_config.jsonTokenizer config. This should be present & have a chat_template field for the Friendli Engine to provide chat APIs
Nospecial_tokens_map.json

General requirements for a dataset

3rd-party account integration

How to integrate a Hugging Face account

If you revoke / invalidate the key, you will have to update the key in order to not disrupt ongoing deployments, or to launch a new inference deployment / fine-tuning job

How to integrate a W&B account

If you revoke / invalidate the key, you will have to update the key in order to not disrupt ongoing deployments, or to launch a new inference deployment / fine-tuning job

Extra: How to upload a safetensors format model to W&B using W&B CLI

wandb artifact put -n project/artifact_id --type model /path/to/dir
  • With all this, the W&B artifact will look like this:

Using 3rd-party model

How to use a W&B artifact as a model

  • Use the full name of the artifact
  • The artifact name must be in the format of: org/project/artifact_id:version

How to use a Hugging Face repository as a model

  • Use the repository id of the model. You may select the entry from the list of autocompleted model repositories.
  • You may choose specific branch, or manually enter a commit hash.

Using W&B with Dedicated Fine-tuning

  • When launching a fine-tuning job, you can designate a W&B project that the metrics will be exported to. If you provide a W&B project name that already exists, your job will be added to that project. Otherwise, a new W&B project will be automatically created in your integrated W&B account. If the project name is not provided, it defaults to “friendliai”.

  • As the training starts, you will be able to see a new “Run” in the project you chose.

  • By clicking the project, you can easily track & monitor the status of the training job.

If new runs are not displayed in your project, please check that the default team is set correctly on W&B user settings.

Troubleshooting

Can’t access the artifact

  • The artifact might be nonexistent, or hidden so that you cannot access it.

You don’t have access to this gated model

  • The repository is gated. Please follow the steps and gain approval from the owner using Hugging Face Hub.

The repository / artifact is invalid

  • The model does not meet the requirements. Please check if the model follows a correct safetensors format.

The architecture is not supported