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nateraw /mistral-7b-openorca:c76d49b8

Input schema

The fields you can use to run this model with an API. If you don’t give a value for a field its default value will be used.

Field Type Default value Description
prompt
string
None
max_new_tokens
integer
512
The maximum number of tokens the model should generate as output.
temperature
number
0.8
The value used to modulate the next token probabilities.
top_p
number
0.95
A probability threshold for generating the output. If < 1.0, only keep the top tokens with cumulative probability >= top_p (nucleus filtering). Nucleus filtering is described in Holtzman et al. (http://arxiv.org/abs/1904.09751).
top_k
integer
50
The number of highest probability tokens to consider for generating the output. If > 0, only keep the top k tokens with highest probability (top-k filtering).
presence_penalty
number
0
Presence penalty
frequency_penalty
number
0
Frequency penalty
prompt_template
string
<|im_start|>system You are MistralOrca, a large language model trained by Alignment Lab AI. Write out your reasoning step-by-step to be sure you get the right answers! <|im_end|> <|im_start|>user {prompt}<|im_end|> <|im_start|>assistant
The template used to format the prompt. The input prompt is inserted into the template using the `{prompt}` placeholder.

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema
{'items': {'type': 'string'},
 'title': 'Output',
 'type': 'array',
 'x-cog-array-display': 'concatenate',
 'x-cog-array-type': 'iterator'}