I’m very interested in understanding how your large language model processes raw pre-training data into its final training format. Specifically, I’d like to ask:
1,.Data Format Conversion:
Is the original text retained in its raw form (e.g., as plain text or structured fields), or is it transformed into other representations (e.g., tokenized IDs, binary encodings, or embeddings)?
2.Field Connection:
How are different fields or data segments connected during preprocessing? For instance, are delimiters (like commas or special tokens) used, or is another method employed?
3.Example Request:
If possible, could you share a simplified example of how a raw input (e.g., a structured climate record) is converted into the format used for training?
Thank you in advance for your time and expertise! I’d greatly appreciate any insights you can provide.
I’m very interested in understanding how your large language model processes raw pre-training data into its final training format. Specifically, I’d like to ask:
1,.Data Format Conversion:
Is the original text retained in its raw form (e.g., as plain text or structured fields), or is it transformed into other representations (e.g., tokenized IDs, binary encodings, or embeddings)?
2.Field Connection:
How are different fields or data segments connected during preprocessing? For instance, are delimiters (like commas or special tokens) used, or is another method employed?
3.Example Request:
If possible, could you share a simplified example of how a raw input (e.g., a structured climate record) is converted into the format used for training?
Thank you in advance for your time and expertise! I’d greatly appreciate any insights you can provide.