finetune runtime: note on Blob import (HF serves .js as non-JS MIME)

setup_53_2d/finetune/cellmap_tfjs_train.js

@@ -3,6 +3,7 @@
 // (finetune/initializers.json gives the byte offset of every initializer), and writes trained weights back into
 // the .onnx bytes in place, so the result is served by onnxruntime-web exactly as before.
 //
+//   (served from Hugging Face this file has no JavaScript MIME type: fetch it and import() a Blob URL, or bundle it)
 //   const g = await (await fetch(base + "finetune/train_graph.json")).json();
 //   const offs = (await (await fetch(base + "finetune/initializers.json")).json())[onnxFile];
 //   const onnxBytes = new Uint8Array(await (await fetch(base + onnxFile)).arrayBuffer());

setup_53_2d/finetune/finetune_spike.html

@@ -14,7 +14,9 @@ const model = q.get("model") || "setup_53_2d", sizes = (q.get("sizes") || "300,5
 const repo = q.get("repo") || "https://huggingface.co/cellmap/onnx-web-models/resolve/main/";
 const base = repo + model + "/";
 const log = s => { document.getElementById("log").textContent += "\n" + s; console.log(s); };
-const rt = await import(base + "finetune/cellmap_tfjs_train.js");
+// HF serves .js without a JavaScript MIME type, so import it from a Blob
+const rt = await import(URL.createObjectURL(new Blob([await (await fetch(base + "finetune/cellmap_tfjs_train.js")).text()],
+                                                     { type: "text/javascript" })));
 await tf.setBackend("webgpu"); await tf.ready();
 const man = await (await fetch(base + "manifest.json")).json();
 const graph = await (await fetch(base + "finetune/train_graph.json")).json();

setup_54_2d/finetune/cellmap_tfjs_train.js

@@ -3,6 +3,7 @@
 // (finetune/initializers.json gives the byte offset of every initializer), and writes trained weights back into
 // the .onnx bytes in place, so the result is served by onnxruntime-web exactly as before.
 //
+//   (served from Hugging Face this file has no JavaScript MIME type: fetch it and import() a Blob URL, or bundle it)
 //   const g = await (await fetch(base + "finetune/train_graph.json")).json();
 //   const offs = (await (await fetch(base + "finetune/initializers.json")).json())[onnxFile];
 //   const onnxBytes = new Uint8Array(await (await fetch(base + onnxFile)).arrayBuffer());

setup_54_2d/finetune/finetune_spike.html

@@ -14,7 +14,9 @@ const model = q.get("model") || "setup_53_2d", sizes = (q.get("sizes") || "300,5
 const repo = q.get("repo") || "https://huggingface.co/cellmap/onnx-web-models/resolve/main/";
 const base = repo + model + "/";
 const log = s => { document.getElementById("log").textContent += "\n" + s; console.log(s); };
-const rt = await import(base + "finetune/cellmap_tfjs_train.js");
+// HF serves .js without a JavaScript MIME type, so import it from a Blob
+const rt = await import(URL.createObjectURL(new Blob([await (await fetch(base + "finetune/cellmap_tfjs_train.js")).text()],
+                                                     { type: "text/javascript" })));
 await tf.setBackend("webgpu"); await tf.ready();
 const man = await (await fetch(base + "manifest.json")).json();
 const graph = await (await fetch(base + "finetune/train_graph.json")).json();