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nateraw /sqlcoder-70b-alpha:d6cd1065
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 |
|---|---|---|---|
| question |
string
|
The question to answer with a SQL query.
|
|
| table_metadata |
string
|
The database schema to use when generating the SQL query.
|
|
| max_new_tokens |
integer
|
512
|
The maximum number of tokens the model should generate as output.
|
| temperature |
number
|
0.7
|
The value used to modulate the next token probabilities.
|
| do_sample |
boolean
|
True
|
Whether or not to use sampling; otherwise use greedy decoding.
|
| 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).
|
| prompt_template |
string
|
### Task
Generate a SQL query to answer [QUESTION]{question}[/QUESTION]
### Instructions
- If you cannot answer the question with the available database schema, return 'I do not know'
### Database Schema
The query will run on a database with the following schema:
{table_metadata}
### Answer
Given the database schema, here is the SQL query that answers [QUESTION]{question}[/QUESTION]
[SQL]
|
The template used to format the prompt before passing it to the model. For no template, you can set this to `{prompt}`.
|
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'}