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zsxkib /qwen2-0.5b-instruct:f45376a2
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
|
Give me a short introduction to large language model.
|
Input prompt
|
| system_prompt |
string
|
You are a helpful assistant.
|
System prompt
|
| model_type |
string
(enum)
|
Qwen2-0.5B-Instruct
Options: Qwen2-0.5B-Instruct, Qwen2-0.5B-Instruct-GPTQ-Int8, Qwen2-0.5B-Instruct-GPTQ-Int4 |
Choose from available 0.5B models
|
| max_new_tokens |
integer
|
512
Min: 1 Max: 32768 |
The maximum number of tokens to generate
|
| temperature |
number
|
1
Min: 0.1 Max: 5 |
Adjusts randomness of outputs, greater than 1 is random and 0 is deterministic, 0.75 is a good starting value.
|
| top_p |
number
|
1
Min: 0.01 Max: 1 |
When decoding text, samples from the top p percentage of most likely tokens; lower to ignore less likely tokens.
|
| top_k |
integer
|
1
|
When decoding text, samples from the top k most likely tokens; lower to ignore less likely tokens.
|
| repetition_penalty |
number
|
1
Min: 0.01 Max: 10 |
Penalty for repeated words in generated text; 1 is no penalty, values greater than 1 discourage repetition, less than 1 encourage it.
|
| seed |
integer
|
The seed for the random number generator
|
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'}