try inference version

sketch.js

@@ -1,12 +1,12 @@
 // connect to API via module
 
 // import { AutoTokenizer, env } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers';
-import { pipeline, env } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers';
-import { oauthLoginUrl, oauthHandleRedirectIfPresent } from 'https://esm.sh/@huggingface/hub';
+// import { pipeline, env } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers';
 
+/// AUTHORIZATION
 
+import { oauthLoginUrl, oauthHandleRedirectIfPresent } from 'https://esm.sh/@huggingface/hub';
 
-/// AUTHORIZATION
 const oauthResult = await oauthHandleRedirectIfPresent();
 
 if (!oauthResult) {
@@ -19,15 +19,13 @@ if (!oauthResult) {
 const HFAUTH = oauthResult.accessToken
 console.log(HFAUTH)
 
-// import { pipeline, env } from 'https://cdn.jsdelivr.net/npm/@xenova/[email protected]';
-// import { HfInference } from 'https://esm.sh/@huggingface/inference';
-// const inference = new HfInference(HFAUTH);
+import { HfInference } from 'https://esm.sh/@huggingface/inference';
+const inference = new HfInference(HFAUTH);
 
 // PIPELINE MODELS
 // models('Xenova/gpt2', 'Xenova/gpt-3.5-turbo', 'mistralai/Mistral-7B-Instruct-v0.2', 'Xenova/llama-68m', 'meta-llama/Meta-Llama-3-8B', 'Xenova/bloom-560m', 'Xenova/distilgpt2')
 // list of models by task: 'https://huggingface.co/docs/transformers.js/index#supported-tasksmodels'
 
-
 // Since we will download the model from the Hugging Face Hub, we can skip the local model check
 // env.allowLocalModels = false;
 
@@ -45,8 +43,6 @@ var blanksArray = []
 // const detector = await pipeline('text-generation', 'meta-llama/Meta-Llama-3-8B', 'Xenova/LaMini-Flan-T5-783M');
 
 
-
-
 ///// p5 STUFF
 
 // create an instance of the p5 class as a workspace for all your p5.js code
@@ -175,35 +171,35 @@ new p5(function (p5) {
 ///// MODEL STUFF
 
 
-// async function runModel(PREPROMPT, PROMPT){
-//     // inference API version
+async function runModel(PREPROMPT, PROMPT){
+    // inference API version
 
-//     let MODELNAME = "HuggingFaceH4/zephyr-7b-beta"
-//     // let MODELNAME = "openai-community/gpt2"
-//     // let MODELNAME = 'mistral_inference'
+    let MODELNAME = "HuggingFaceH4/zephyr-7b-beta"
+    // let MODELNAME = "openai-community/gpt2"
+    // let MODELNAME = 'mistral_inference'
     
-//     let out = await inference.textGeneration({    
-//         model: MODELNAME,
-//         messages: [{ 
-//                     role: "system", 
-//                     content: PREPROMPT
-//                 },{
-//                     role: "user",
-//                     content: PROMPT
-//                 }],
-//         max_new_tokens: 150
-//     });
+    let out = await inference.textGeneration({    
+        model: MODELNAME,
+        messages: [{ 
+                    role: "system", 
+                    content: PREPROMPT
+                },{
+                    role: "user",
+                    content: PROMPT
+                }],
+        max_new_tokens: 128
+    });
 
-//     console.log(out)
+    console.log(out)
 
-//     // modelResult = await out.messages[0].content
+    // modelResult = await out.messages[0].content
 
-//     var modelResult = await out.choices[0].message.content
-//     // var modelResult = await out[0].generated_text
-//     console.log(modelResult);
+    var modelResult = await out.choices[0].message.content
+    // var modelResult = await out[0].generated_text
+    console.log(modelResult);
 
-//     return modelResult
-// }
+    return modelResult
+}
 
 
     //inference.fill_mask({
@@ -234,57 +230,57 @@ new p5(function (p5) {
 
 
 
-async function runModel(PREPROMPT, PROMPT){
-    // // pipeline version
+// async function runModel(PREPROMPT, PROMPT){
+//     // // pipeline version
 
-    // let MODELNAME = 'mistralai/Mistral-Nemo-Instruct-2407'
-    let MODELNAME = "HuggingFaceH4/zephyr-7b-beta"
+//     // let MODELNAME = 'mistralai/Mistral-Nemo-Instruct-2407'
+//     let MODELNAME = "HuggingFaceH4/zephyr-7b-beta"
 
-    // HFAUTH
+//     // HFAUTH
 
-    // 'meta-llama/Meta-Llama-3-70B-Instruct'
-    // 'openai-community/gpt2'
-    // 'Xenova/gpt-3.5-turbo'
-    // , 'Xenova/distilgpt2'
-    // 'mistralai/Mistral-7B-Instruct-v0.2'
-    // 'HuggingFaceH4/zephyr-7b-beta'
+//     // 'meta-llama/Meta-Llama-3-70B-Instruct'
+//     // 'openai-community/gpt2'
+//     // 'Xenova/gpt-3.5-turbo'
+//     // , 'Xenova/distilgpt2'
+//     // 'mistralai/Mistral-7B-Instruct-v0.2'
+//     // 'HuggingFaceH4/zephyr-7b-beta'
 
-    // pipeline/transformers version
-    let pipe = await pipeline('text-generation', {
-        model: MODELNAME,
-        accessToken: HFAUTH
-    });
-    // seems to work with default model distilgpt2 ugh
+//     // pipeline/transformers version
+//     let pipe = await pipeline('text-generation', {
+//         model: MODELNAME,
+//         accessToken: HFAUTH
+//     });
+//     // seems to work with default model distilgpt2 ugh
     
     
-    // let out = await pipe(inputText, {
-    //     max_tokens: 250,
-    //     return_full_text: false
-    //     // repetition_penalty: 1.5,
-    //     // num_return_sequences: 1 //must be 1 for greedy search
-    // })
+//     // let out = await pipe(inputText, {
+//     //     max_tokens: 250,
+//     //     return_full_text: false
+//     //     // repetition_penalty: 1.5,
+//     //     // num_return_sequences: 1 //must be 1 for greedy search
+//     // })
 
-    // let inputText = PREPROMPT + PROMPT
+//     // let inputText = PREPROMPT + PROMPT
 
-    // let out = await pipe(inputText)
+//     // let out = await pipe(inputText)
 
-    let out = await pipe({    
-        messages: [{ 
-                role: "system", 
-                content: PREPROMPT
-            },{
-                role: "user",
-                content: PROMPT
-            }],
-        max_new_tokens: 100
-    });
+//     let out = await pipe({    
+//         messages: [{ 
+//                 role: "system", 
+//                 content: PREPROMPT
+//             },{
+//                 role: "user",
+//                 content: PROMPT
+//             }],
+//         max_new_tokens: 100
+//     });
     
-    console.log(out)
+//     console.log(out)
     
-    var modelResult = await out.choices[0].message.content
-    // var modelResult = await out[0].generated_text
-    console.log(modelResult)
+//     var modelResult = await out.choices[0].message.content
+//     // var modelResult = await out[0].generated_text
+//     console.log(modelResult)
 
-    return modelResult
+//     return modelResult
 
-}
+// }

tutorial.md

@@ -21,7 +21,7 @@ Part 3: [Training Dataset Explorer]
 Part 4: [Machine Learning Model Inspector & Poetry Machine]
 Part 5: [Putting Critical Tools into Practice]
 
-The code and content in this tutorial build on information from the prior tutorial to start creating your first tool for your p5.js Critical AI Kit. It also builds on fantastic work on critical prompt programming by Yasmin Morgan (2022), Katy Gero (2023), and Minne Atairu (2024).
+The code and content in this tutorial build on information from the prior tutorial to start creating your first tool for your p5.js Critical AI Kit. It also builds on fantastic work on critical prompt programming by Yasmin Morgan (2022), Katy Gero et al.(2024), and Minne Atairu (2024).
 
 ## Why compare prompts?
 
@@ -129,7 +129,7 @@ Consider making it a habit to add text like "AI generated" to the title of any c
 
 ## References
 
-> Ref Katy's project (Gero 2023).
+Katy Ilonka Gero, Chelse Swoopes, Ziwei Gu, Jonathan K. Kummerfeld, and Elena L. Glassman. 2024. Supporting Sensemaking of Large Language Model Outputs at Scale. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI '24). Association for Computing Machinery, New York, NY, USA, Article 838, 1–21. https://doi.org/10.1145/3613904.3642139
 
 Morgan, Yasmin. 2022. "AIxDesign Icebreakers, Mini-Games & Interactive Exercises." https://aixdesign.co/posts/ai-icebreakers-mini-games-interactive-exercises