bigframes.ml.llm.Claude3TextGenerator.predict#

Claude3TextGenerator.predict(X: DataFrame | Series | DataFrame | Series, *, max_output_tokens: int = 128, top_k: int = 40, top_p: float = 0.95, max_retries: int = 0) → DataFrame[source]#

Predict the result from input DataFrame.

Parameters:

  • X (bigframes.dataframe.DataFrame or bigframes.series.Series or pandas.core.frame.DataFrame or pandas.core.series.Series) – Input DataFrame or Series, can contain one or more columns. If multiple columns are in the DataFrame, it must contain a “prompt” column for prediction. Prompts can include preamble, questions, suggestions, instructions, or examples.

  • max_output_tokens (int, default 128) – Maximum number of tokens that can be generated in the response. Specify a lower value for shorter responses and a higher value for longer responses. A token may be smaller than a word. A token is approximately four characters. 100 tokens correspond to roughly 60-80 words. Default 128. Possible values are in the range [1, 4096].

  • top_k (int, default 40) – Top-k changes how the model selects tokens for output. A top-k of 1 means the selected token is the most probable among all tokens in the model’s vocabulary (also called greedy decoding), while a top-k of 3 means that the next token is selected from among the 3 most probable tokens (using temperature). For each token selection step, the top K tokens with the highest probabilities are sampled. Then tokens are further filtered based on topP with the final token selected using temperature sampling. Specify a lower value for less random responses and a higher value for more random responses. Default 40. Possible values [1, 40].

  • top_p (float, default 0.95) – Top-p changes how the model selects tokens for output. Tokens are selected from most K (see topK parameter) probable to least until the sum of their probabilities equals the top-p value. For example, if tokens A, B, and C have a probability of 0.3, 0.2, and 0.1 and the top-p value is 0.5, then the model will select either A or B as the next token (using temperature) and not consider C at all. Specify a lower value for less random responses and a higher value for more random responses. Default 0.95. Possible values [0.0, 1.0].

  • max_retries (int, default 0) – Max number of retries if the prediction for any rows failed. Each try needs to make progress (i.e. has successfully predicted rows) to continue the retry. Each retry will append newly succeeded rows. When the max retries are reached, the remaining rows (the ones without successful predictions) will be appended to the end of the result.

Returns:

DataFrame of shape (n_samples, n_input_columns + n_prediction_columns). Returns predicted values.

Return type:

bigframes.dataframe.DataFrame