Bolden config items

docs/genai/reference/config.md

@@ -79,73 +79,73 @@ A configuration file called genai_config.json is generated automatically if the
 
 #### General model config
 
-* _type_: The type of model. Can be phi, llama or gpt.
+* **_type_**: The type of model. Can be phi, llama or gpt.
 
-* _vocab_size_: The size of the vocabulary that the model processes ie the number of tokens in the vocabulary.
+* **_vocab_size_**: The size of the vocabulary that the model processes ie the number of tokens in the vocabulary.
 
-* _bos_token_id_: The id of the beginning of sequence token.
+* **_bos_token_id_**: The id of the beginning of sequence token.
 
-* _eos_token_id_: The id of the end of sequence token.
+* **_eos_token_id_**: The id of the end of sequence token.
 
-* _pad_token_: The id of the padding token.
+* **_pad_token_**: The id of the padding token.
 
-* _context_length_: The maxinum length of sequence that the model can process.
+* **_context_length_**: The maxinum length of sequence that the model can process.
 
 
 #### Session options
 
 These are the options that are passed to ONNX Runtime, which runs the model on each token generation iteration.
 
-* _provider_options_: a priortized list of execution targets on which to run the model. If running on CPU, this option is not present. A list of execution provider specific configurations can be specified inside the provider item.
+* **_provider_options_**: a priortized list of execution targets on which to run the model. If running on CPU, this option is not present. A list of execution provider specific configurations can be specified inside the provider item.
 
-* _log_id_: a prefix to output when logging
+* **_log_id_**: a prefix to output when logging
 
 
 Then For each model in the pipeline there is one section, named by the model. 
 
 #### Decoder model config
 
-* _filename_: The name of the model file.
+* **_filename_**: The name of the model file.
 
-* _inputs_: The names of each of the inputs. Sequences of model inputs can contain a wildcard representing the index in the sequence.
+* **_inputs_**: The names of each of the inputs. Sequences of model inputs can contain a wildcard representing the index in the sequence.
 
-* _outputs_: The names of each of the outputs.
+* **_outputs_**: The names of each of the outputs.
 
-* _num_attention_heads: The number of attention heads in the model.
+* **_num_attention_heads_**: The number of attention heads in the model.
 
-* _head_size_: The size of the attention heads.
+* **_head_size_**: The size of the attention heads.
 
-* _hidden_size_: The size of the hidden layers.
+* **_hidden_size_**: The size of the hidden layers.
 
-* _num_key_value_heads_: The number of key value heads.
+* **_num_key_value_heads_**: The number of key value heads.
 
 
-### Search section
+### Generation search section
 
-* _max_length_: The maximum length that the model will generate.
+* **_max_length_**: The maximum length that the model will generate.
 
-* _min_length_: The minimum length that the model will generate.
+* **_min_length_**: The minimum length that the model will generate.
 
-* _do_sample_: 
+* **_do_sample_**: 
 
-* _num_beams_: The number of beams to apply when generating the output sequence using beam search. If num_beams=1, then generation is performed using greedy search.
+* **_num_beams_**: The number of beams to apply when generating the output sequence using beam search. If num_beams=1, then generation is performed using greedy search.
 
-* _early_stopping_ :  Whether to stop the beam search when at least num_beams sentences are finished per batch or not. Defaults to false.
+* **_early_stopping_**:  Whether to stop the beam search when at least num_beams sentences are finished per batch or not. Defaults to false.
 
-* _num_sequences_: The number of sequences to generate. Returns the sequences with the highest scores in order.
+* **_num_sequences_**: The number of sequences to generate. Returns the sequences with the highest scores in order.
 
-* _temperature_: The temperature value scales the probability of each token so that probable tokens become more likely while less probable ones become less likely. This value can have a range  0 < `temperature` ≤ 1. When temperature is equal to `1`, it has no effect.
+* **_temperature_**: The temperature value scales the probability of each token so that probable tokens become more likely while less probable ones become less likely. This value can have a range  0 < `temperature` ≤ 1. When temperature is equal to `1`, it has no effect.
 
-* _top_k_: Only includes tokens that do fall within the list of the `K` most probable tokens.
+* **_top_k_**: Only includes tokens that do fall within the list of the `K` most probable tokens.
 
-* _top_p_: Only includes the most probable tokens with probabilities that add up to `P` or higher. Defaults to `1`, which includes all of the tokens.
+* **_top_p_**: Only includes the most probable tokens with probabilities that add up to `P` or higher. Defaults to `1`, which includes all of the tokens.
 
-* _repetition_penalty_: Discounts the scores of previously generated tokens if set to a value greater than `1`. Defaults to `1`. 
+* **_repetition_penalty_**: Discounts the scores of previously generated tokens if set to a value greater than `1`. Defaults to `1`. 
 
-* _length_penalty_: Controls the length of the output generated. Value less than `1` encourages the generation to produce shorter sequences. Values greater than `1` encourages longer sequences. Defaults to `1`.
+* **_length_penalty_**: Controls the length of the output generated. Value less than `1` encourages the generation to produce shorter sequences. Values greater than `1` encourages longer sequences. Defaults to `1`.
 
-* _diversity_penalty_: 
+* **_diversity_penalty_**: 
 
-* _no_repeat_ngram_size_: 
+* **_no_repeat_ngram_size_**: 
 
-* _past_present_share_buffer_: If set to true, the past and present buffer are shared for efficiency. 
+* **_past_present_share_buffer_**: If set to true, the past and present buffer are shared for efficiency.