try with top_k roberta model

README.md

@@ -12,6 +12,7 @@ hf_oauth_scopes:
   - inference-api
 models:
 - bert-base-uncased
+- distilroberta-base
 # - gpt-3.5-turbo
 # - bigscience/bloom-560m
 # - Xenova/distilgpt2

sketch.js

@@ -77,7 +77,7 @@ new p5(function (p5) {
         // promptInput.position(0,160)
         promptInput.size(600);
         promptInput.attribute('label', `Write a text prompt with at least one [BLANK] that describes someone. You can also write [FILL] where you want the bot to fill in a word on its own.`)
-        promptInput.value(`The [BLANK] works as a [MASK] but ...`)
+        promptInput.value(`The [BLANK] works as a [mask] but ...`)
         promptInput.addClass("prompt")
         p5.createP(promptInput.attribute('label'))
             // .position(0,100)
@@ -158,7 +158,6 @@ new p5(function (p5) {
     //     // Please return an array of sentences based on the sample sentence to follow. In each sentence, 
 
     //     // let modelResult = await runModel(PREPROMPT, PROMPT)
-    //     let modelResult = await runModel(BLANKSVALUES, PROMPT)
 
     //     await displayModel(modelResult)
     // }
@@ -166,33 +165,36 @@ new p5(function (p5) {
     // creating multiple prompt inputs rather than instructing model to do so
     async function getInputs(){
         // Map the list of blanks text values to a new list
-        let BLANKSVALUES = blanksArray.map(i => i.value())
-        console.log(BLANKSVALUES)
+        // let BLANKSVALUES = blanksArray.map(i => i.value())
+        // console.log(BLANKSVALUES)
         
         // Do model stuff in this function instead of in general
         let PROMPT = promptInput.value() // updated check of the prompt field
         
         // BLANKS = inputValues // get ready to feed array list into model
 
-        let PROMPTS = []
-        for (let b in BLANKSVALUES){
-            console.log(BLANKSVALUES[b])
-            let p = PROMPT.replace('[BLANK]', `${BLANKSVALUES[b]}`)
-            console.log(p)
-            PROMPTS.push(p)
-        }
-        console.log(PROMPTS)
+        // for running MULTIPLE PROMPTS AT ONCE
+        // let PROMPTS = []
+        // for (let b in BLANKSVALUES){
+        //     console.log(BLANKSVALUES[b])
+        //     let p = PROMPT.replace('[BLANK]', `${BLANKSVALUES[b]}`)
+        //     console.log(p)
+        //     PROMPTS.push(p)
+        // }
+        // console.log(PROMPTS)
 
         // let PREPROMPT = `In the sentence I provide, please fill in the [BLANK] with each word in the array ${BLANKSVALUES}, replace any [MASK] with a word of your choice. Here is the SAMPLE SENTENCE: ` 
 
         // we pass PROMPT and PREPROMPT to the model function, don't need to pass BLANKSVALUES bc it's passed into the PREPROMPT already here
 
         // Please return an array of sentences based on the sample sentence to follow. In each sentence, 
-
+        
+        let modelResult = await runModel(PROMPT)
         // let modelResult = await runModel(PREPROMPT, PROMPT)
-        let modelResult = await runModel(PROMPTS)
-
-        await displayModel(resultsArray[0], resultsArray[1])
+        // let modelResult = await runModel(PROMPTS)
+        
+        await displayModel(modelResult)
+        // await displayModel(resultsArray[0], resultsArray[1])
     }
 
     async function displayModel(m){
@@ -346,20 +348,28 @@ new p5(function (p5) {
 // }
 
 
-async function runModel(PROMPTS){
+// async function runModel(PROMPTS){
+async function runModel(PROMPT){
 
-    let MODELNAME = "bert-base-uncased"
+    // let MODELNAME = "bert-base-uncased"
+    let MODELNAME = 'distilroberta-base'
 
-    let unmasker = await pipeline('fill-mask', 'bert-base-uncased')
+    let unmasker = await pipeline('fill-mask', MODELNAME)
 
-    for (let p in PROMPTS){
-        var res = unmasker(p)
-        console.log(res)
+    let res = unmasker(PROMPT, top_k=5)
 
-        var modelResult = res[0].token_str
-        console.log(modelResult)
+    var modelResult = res
 
-        resultsArray.push(modelResult)
-    }
-    return resultsArray
+    return modelResult
+
+    // for (let p in PROMPTS){
+    //     var res = unmasker(p)
+    //     console.log(res)
+
+    //     var modelResult = res[0].token_str
+    //     console.log(modelResult)
+
+    //     resultsArray.push(modelResult)
+    // }
+    // return resultsArray
 }