switch back to inference from pipeline

sketch.js

@@ -1,8 +1,8 @@
-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 { 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();
 
-let pipe = await pipeline('text-generation', 'mistralai/Mistral-7B-Instruct-v0.2');
+// let pipe = await pipeline('text-generation', 'mistralai/Mistral-7B-Instruct-v0.2');
 // 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'
 
@@ -20,26 +20,27 @@ var PREPROMPT = `Return an array of sentences. In each sentence, fill in the [BL
 var PROMPT = `The [BLANK] works as a [FILL] but wishes for [FILL].`
 
 // Chat completion API
-// const out = await inference.chatCompletion({
-//     model: "mistralai/Mistral-7B-Instruct-v0.2",
-//     // model: "google/gemma-2-9b",
-//     messages: [{ role: "user", content: PREPROMPT + PROMPT }],
-//     max_tokens: 100
-//   });
+const out = await inference.chatCompletion({
+    model: "mistralai/Mistral-7B-Instruct-v0.2",
+    // model: "google/gemma-2-9b",
+    messages: [{ role: "user", content: PREPROMPT + PROMPT }],
+    max_tokens: 100
+  });
 
 // let out = await pipe(PREPROMPT + PROMPT)
-let out = await pipe(PREPROMPT + PROMPT, {
-    max_new_tokens: 250,
-    temperature: 0.9,
-    // return_full_text: False,
-    repetition_penalty: 1.5,
-    // no_repeat_ngram_size: 2,
-    // num_beams: 2,
-    num_return_sequences: 1
-});
+// let out = await pipe(PREPROMPT + PROMPT, {
+//     max_new_tokens: 250,
+//     temperature: 0.9,
+//     // return_full_text: False,
+//     repetition_penalty: 1.5,
+//     // no_repeat_ngram_size: 2,
+//     // num_beams: 2,
+//     num_return_sequences: 1
+// });
 console.log(out)
 
-var result = await out[0].generated_text
+var result = await out.choices[0].message
+// var result = await out[0].generated_text
 console.log(result);