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deepseek-ai /deepseek-67b-base:0f246960
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
|
An attention function can be described as mapping a query and a set of key-value pairs to an output, where the query, keys, values, and output are all vectors. The output is
|
Input prompt
|
| max_new_tokens |
integer
|
256
Min: 1 Max: 4096 |
The maximum number of tokens the model should generate as output.
|
| temperature |
number
|
0.7
|
The value used to modulate the next token probabilities.
|
| top_p |
number
|
0.8
|
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).
|
| repetition_penalty |
number
|
1.05
|
Repetition penalty
|
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'}