try inference with Oauth

sketch.js

@@ -1,10 +1,24 @@
 // 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 { pipeline, env } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers';
+import { oauthLoginUrl, oauthHandleRedirectIfPresent } from 'https://esm.sh/@huggingface/hub';
+
+const oauthResult = await oauthHandleRedirectIfPresent();
+
+if (!oauthResult) {
+  // If the user is not logged in, redirect to the login page
+  window.location.href = await oauthLoginUrl();
+}
+
+// You can use oauthResult.accessToken, oauthResult.accessTokenExpiresAt and oauthResult.userInfo
+console.log(oauthResult);
+const HF_TOKEN = oauthResult
+
 // import { pipeline, env } from 'https://cdn.jsdelivr.net/npm/@xenova/[email protected]';
 // import { HfInference } from 'https://cdn.jsdelivr.net/npm/@huggingface/[email protected]/+esm';
-// const inference = new HfInference();
+import { HfInference } from 'https://esm.sh/@huggingface/inference';
+const inference = new HfInference(HF_TOKEN);
 
 // 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')
@@ -12,7 +26,7 @@ import { pipeline, env } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers
 
 
 // Since we will download the model from the Hugging Face Hub, we can skip the local model check
-env.allowLocalModels = false;
+// env.allowLocalModels = false;
 
 ///////// VARIABLES 
 
@@ -157,72 +171,82 @@ new p5(function (p5) {
 
 ///// MODEL STUFF
 
-async function runModel(PREPROMPT, PROMPT){
-    // // Chat completion API
+// async function runModel(PREPROMPT, PROMPT){
+//     // // Chat completion API
 
-    let MODELNAME = 'mistralai/Mistral-Nemo-Instruct-2407'
+//     let MODELNAME = 'mistralai/Mistral-Nemo-Instruct-2407'
 
-    // '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', MODELNAME);
-    // seems to work with default model distilgpt2 ugh
+//     // pipeline/transformers version
+//     let pipe = await pipeline('text-generation', MODELNAME);
+//     // 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 inputText = PREPROMPT + PROMPT
-
-    // 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(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 out = await pipe(inputText)
+
+//     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[0].generated_text
-    console.log(modelResult)
+//     var modelResult = await out[0].generated_text
+//     console.log(modelResult)
 
-    return modelResult
-
-}
+//     return modelResult
 
+// }
 
+async function runModel(PREPROMPT, PROMPT){
     // inference API version, not working in spaces
-    // const out = await inference.chatCompletion({    
-    //     model: MODELNAME,
-    //     messages: [{ role: "user", content: PREPROMPT + PROMPT }],
-    //     max_tokens: 100
-    // });
 
-    // console.log(out)
+    // let MODELNAME = 'mistralai/Mistral-Nemo-Instruct-2407'
+    let MODELNAME = "mistralai/Mistral-7B-Instruct-v0.2"
+    
+    let out = await inference.chatCompletion({    
+        model: MODELNAME,
+        messages: [{ 
+                    role: "system", 
+                    content: PREPROMPT
+                },{
+                    role: "user",
+                    content: PROMPT
+                }],
+        max_tokens: 100
+    });
 
-    // // modelResult = await out.messages[0].content
+    console.log(out)
 
-    // var modelResult = await out.choices[0].message.content
-    // // var modelResult = await out[0].generated_text
-    // console.log(modelResult);
+    // modelResult = await out.messages[0].content
 
-    // return modelResult
+    var modelResult = await out.choices[0].message.content
+    // var modelResult = await out[0].generated_text
+    console.log(modelResult);
 
+    return modelResult
+}
 
 
     //inference.fill_mask({