fofr
/
mario
mario-flan – Flan XL trained on the Super Mario fandom wiki
- Public
- 62 runs
Run fofr/mario with an API
Use one of our client libraries to get started quickly. Clicking on a library will take you to the Playground tab where you can tweak different inputs, see the results, and copy the corresponding code to use in your own project.
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
|
Prompt to send to FLAN-T5.
|
|
| max_length |
integer
|
50
Min: 1 |
Maximum number of tokens to generate. A word is generally 2-3 tokens
|
| temperature |
number
|
0.75
Min: 0.01 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
|
| repetition_penalty |
number
|
1
Min: 0.01 Max: 5 |
Penalty for repeated words in generated text; 1 is no penalty, values greater than 1 discourage repetition, less than 1 encourage it.
|
| debug |
boolean
|
False
|
provide debugging output in logs
|
{
"type": "object",
"title": "Input",
"required": [
"prompt"
],
"properties": {
"debug": {
"type": "boolean",
"title": "Debug",
"default": false,
"x-order": 5,
"description": "provide debugging output in logs"
},
"top_p": {
"type": "number",
"title": "Top P",
"default": 1,
"maximum": 1,
"minimum": 0.01,
"x-order": 3,
"description": "When decoding text, samples from the top p percentage of most likely tokens; lower to ignore less likely tokens"
},
"prompt": {
"type": "string",
"title": "Prompt",
"x-order": 0,
"description": "Prompt to send to FLAN-T5."
},
"max_length": {
"type": "integer",
"title": "Max Length",
"default": 50,
"minimum": 1,
"x-order": 1,
"description": "Maximum number of tokens to generate. A word is generally 2-3 tokens"
},
"temperature": {
"type": "number",
"title": "Temperature",
"default": 0.75,
"maximum": 5,
"minimum": 0.01,
"x-order": 2,
"description": "Adjusts randomness of outputs, greater than 1 is random and 0 is deterministic, 0.75 is a good starting value."
},
"repetition_penalty": {
"type": "number",
"title": "Repetition Penalty",
"default": 1,
"maximum": 5,
"minimum": 0.01,
"x-order": 4,
"description": "Penalty for repeated words in generated text; 1 is no penalty, values greater than 1 discourage repetition, less than 1 encourage it."
}
}
}
Output schema
The shape of the response you’ll get when you run this model with an API.
{
"type": "array",
"items": {
"type": "string"
},
"title": "Output",
"x-cog-array-type": "iterator",
"x-cog-array-display": "concatenate"
}