@huggingface/tasks - npm Package Compare versions

Comparing version 0.19.26 to 0.19.27

dist/commonjs/model-libraries-snippets.js

@@ -1331,5 +1331,5 @@ "use strict";
     const remote_code_snippet = model.tags.includes(TAG_CUSTOM_CODE) ? ", trust_remote_code=True" : "";
-    let autoSnippet;
+    const autoSnippet = [];
     if (info.processor) {
-        const varName = info.processor === "AutoTokenizer"
+        const processorVarName = info.processor === "AutoTokenizer"
             ? "tokenizer"
@@ -1339,16 +1339,23 @@ : info.processor === "AutoFeatureExtractor"
                 : "processor";
-        autoSnippet = [
-            "# Load model directly",
-            `from transformers import ${info.processor}, ${info.auto_model}`,
-            "",
-            `${varName} = ${info.processor}.from_pretrained("${model.id}"` + remote_code_snippet + ")",
-            `model = ${info.auto_model}.from_pretrained("${model.id}"` + remote_code_snippet + ")",
-        ].join("\n");
+        autoSnippet.push("# Load model directly", `from transformers import ${info.processor}, ${info.auto_model}`, "", `${processorVarName} = ${info.processor}.from_pretrained("${model.id}"` + remote_code_snippet + ")", `model = ${info.auto_model}.from_pretrained("${model.id}"` + remote_code_snippet + ")");
+        if (model.tags.includes("conversational")) {
+            if (model.tags.includes("image-text-to-text")) {
+                autoSnippet.push("messages = [", [
+                    "    {",
+                    '        "role": "user",',
+                    '        "content": [',
+                    '            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},',
+                    '            {"type": "text", "text": "What animal is on the candy?"}',
+                    "        ]",
+                    "    },",
+                ].join("\n"), "]");
+            }
+            else {
+                autoSnippet.push("messages = [", '    {"role": "user", "content": "Who are you?"},', "]");
+            }
+            autoSnippet.push("inputs = ${processorVarName}.apply_chat_template(", "	messages,", "	add_generation_prompt=True,", "	tokenize=True,", "	return_dict=True,", '	return_tensors="pt",', ").to(model.device)", "", "outputs = model.generate(**inputs, max_new_tokens=40)", 'print(${processorVarName}.decode(outputs[0][inputs["input_ids"].shape[-1]:]))');
+        }
     }
     else {
-        autoSnippet = [
-            "# Load model directly",
-            `from transformers import ${info.auto_model}`,
-            `model = ${info.auto_model}.from_pretrained("${model.id}"` + remote_code_snippet + ")",
-        ].join("\n");
+        autoSnippet.push("# Load model directly", `from transformers import ${info.auto_model}`, `model = ${info.auto_model}.from_pretrained("${model.id}"` + remote_code_snippet + ', torch_dtype="auto"),');
     }
@@ -1386,5 +1393,5 @@ if (model.pipeline_tag && library_to_tasks_js_1.LIBRARY_TASK_MAPPING.transformers?.includes(model.pipeline_tag)) {
         }
-        return [pipelineSnippet.join("\n"), autoSnippet];
+        return [pipelineSnippet.join("\n"), autoSnippet.join("\n")];
     }
-    return [autoSnippet];
+    return [autoSnippet.join("\n")];
 };
@@ -1391,0 +1398,0 @@ exports.transformers = transformers;

dist/commonjs/model-libraries.d.ts

@@ -521,2 +521,9 @@ import type { ModelData } from "./model-data.js";
     };
+    kronos: {
+        prettyLabel: string;
+        repoName: string;
+        repoUrl: string;
+        filter: false;
+        countDownloads: string;
+    };
     k2: {
@@ -1193,3 +1200,3 @@ prettyLabel: string;
 export declare const ALL_MODEL_LIBRARY_KEYS: ModelLibraryKey[];
-export declare const ALL_DISPLAY_MODEL_LIBRARY_KEYS: ("acestep" | "adapter-transformers" | "allennlp" | "anemoi" | "araclip" | "asteroid" | "audiocraft" | "audioseal" | "bagel-mot" | "ben2" | "bertopic" | "big_vision" | "birder" | "birefnet" | "bm25s" | "champ" | "chatterbox" | "chat_tts" | "colpali" | "comet" | "contexttab" | "cosmos" | "cxr-foundation" | "deepforest" | "depth-anything-v2" | "depth-pro" | "derm-foundation" | "describe-anything" | "dia-tts" | "diffree" | "diffusers" | "diffusionkit" | "doctr" | "cartesia_pytorch" | "cartesia_mlx" | "clipscope" | "cosyvoice" | "cotracker" | "edsnlp" | "elm" | "espnet" | "fairseq" | "fastai" | "fasttext" | "flair" | "fme" | "gemma.cpp" | "geometry-crafter" | "gliner" | "glyph-byt5" | "grok" | "hallo" | "hermes" | "hezar" | "htrflow" | "hunyuan-dit" | "hunyuan3d-2" | "imstoucan" | "index-tts" | "infinite-you" | "keras" | "tf-keras" | "keras-hub" | "kimi-audio" | "k2" | "lightning-ir" | "litert-lm" | "lerobot" | "liveportrait" | "llama-cpp-python" | "mini-omni2" | "mindspore" | "magi-1" | "magenta-realtime" | "mamba-ssm" | "mars5-tts" | "matanyone" | "mesh-anything" | "merlin" | "medvae" | "mitie" | "ml-agents" | "mlx" | "mlx-image" | "mlc-llm" | "model2vec" | "moshi" | "mtvcraft" | "nemo" | "open-oasis" | "open_clip" | "open-sora" | "outetts" | "paddlenlp" | "PaddleOCR" | "peft" | "perception-encoder" | "phantom-wan" | "pxia" | "pyannote-audio" | "py-feat" | "pythae" | "recurrentgemma" | "relik" | "refiners" | "renderformer" | "reverb" | "saelens" | "sam2" | "sample-factory" | "sapiens" | "seedvr" | "sentence-transformers" | "setfit" | "sklearn" | "spacy" | "span-marker" | "speechbrain" | "ssr-speech" | "stable-audio-tools" | "monkeyocr" | "diffusion-single-file" | "seed-story" | "soloaudio" | "stable-baselines3" | "stanza" | "swarmformer" | "f5-tts" | "genmo" | "tencent-song-generation" | "tensorflowtts" | "tabpfn" | "terratorch" | "tic-clip" | "timesfm" | "timm" | "tirex" | "torchgeo" | "transformers" | "transformers.js" | "trellis" | "ultralytics" | "univa" | "uni-3dar" | "unity-sentis" | "sana" | "videoprism" | "vfi-mamba" | "voicecraft" | "vui" | "wham" | "whisperkit" | "yolov10" | "zonos" | "3dtopia-xl")[];
+export declare const ALL_DISPLAY_MODEL_LIBRARY_KEYS: ("acestep" | "adapter-transformers" | "allennlp" | "anemoi" | "araclip" | "asteroid" | "audiocraft" | "audioseal" | "bagel-mot" | "ben2" | "bertopic" | "big_vision" | "birder" | "birefnet" | "bm25s" | "champ" | "chatterbox" | "chat_tts" | "colpali" | "comet" | "contexttab" | "cosmos" | "cxr-foundation" | "deepforest" | "depth-anything-v2" | "depth-pro" | "derm-foundation" | "describe-anything" | "dia-tts" | "diffree" | "diffusers" | "diffusionkit" | "doctr" | "cartesia_pytorch" | "cartesia_mlx" | "clipscope" | "cosyvoice" | "cotracker" | "edsnlp" | "elm" | "espnet" | "fairseq" | "fastai" | "fasttext" | "flair" | "fme" | "gemma.cpp" | "geometry-crafter" | "gliner" | "glyph-byt5" | "grok" | "hallo" | "hermes" | "hezar" | "htrflow" | "hunyuan-dit" | "hunyuan3d-2" | "imstoucan" | "index-tts" | "infinite-you" | "keras" | "tf-keras" | "keras-hub" | "kimi-audio" | "kronos" | "k2" | "lightning-ir" | "litert-lm" | "lerobot" | "liveportrait" | "llama-cpp-python" | "mini-omni2" | "mindspore" | "magi-1" | "magenta-realtime" | "mamba-ssm" | "mars5-tts" | "matanyone" | "mesh-anything" | "merlin" | "medvae" | "mitie" | "ml-agents" | "mlx" | "mlx-image" | "mlc-llm" | "model2vec" | "moshi" | "mtvcraft" | "nemo" | "open-oasis" | "open_clip" | "open-sora" | "outetts" | "paddlenlp" | "PaddleOCR" | "peft" | "perception-encoder" | "phantom-wan" | "pxia" | "pyannote-audio" | "py-feat" | "pythae" | "recurrentgemma" | "relik" | "refiners" | "renderformer" | "reverb" | "saelens" | "sam2" | "sample-factory" | "sapiens" | "seedvr" | "sentence-transformers" | "setfit" | "sklearn" | "spacy" | "span-marker" | "speechbrain" | "ssr-speech" | "stable-audio-tools" | "monkeyocr" | "diffusion-single-file" | "seed-story" | "soloaudio" | "stable-baselines3" | "stanza" | "swarmformer" | "f5-tts" | "genmo" | "tencent-song-generation" | "tensorflowtts" | "tabpfn" | "terratorch" | "tic-clip" | "timesfm" | "timm" | "tirex" | "torchgeo" | "transformers" | "transformers.js" | "trellis" | "ultralytics" | "univa" | "uni-3dar" | "unity-sentis" | "sana" | "videoprism" | "vfi-mamba" | "voicecraft" | "vui" | "wham" | "whisperkit" | "yolov10" | "zonos" | "3dtopia-xl")[];
 //# sourceMappingURL=model-libraries.d.ts.map

dist/commonjs/model-libraries.js

@@ -519,2 +519,9 @@ "use strict";
     },
+    kronos: {
+        prettyLabel: "KRONOS",
+        repoName: "KRONOS",
+        repoUrl: "https://github.com/mahmoodlab/KRONOS",
+        filter: false,
+        countDownloads: `path_extension:"pt"`,
+    },
     k2: {
@@ -521,0 +528,0 @@ prettyLabel: "K2",

dist/esm/model-libraries-snippets.js

@@ -1262,5 +1262,5 @@ import { LIBRARY_TASK_MAPPING } from "./library-to-tasks.js";
     const remote_code_snippet = model.tags.includes(TAG_CUSTOM_CODE) ? ", trust_remote_code=True" : "";
-    let autoSnippet;
+    const autoSnippet = [];
     if (info.processor) {
-        const varName = info.processor === "AutoTokenizer"
+        const processorVarName = info.processor === "AutoTokenizer"
             ? "tokenizer"
@@ -1270,16 +1270,23 @@ : info.processor === "AutoFeatureExtractor"
                 : "processor";
-        autoSnippet = [
-            "# Load model directly",
-            `from transformers import ${info.processor}, ${info.auto_model}`,
-            "",
-            `${varName} = ${info.processor}.from_pretrained("${model.id}"` + remote_code_snippet + ")",
-            `model = ${info.auto_model}.from_pretrained("${model.id}"` + remote_code_snippet + ")",
-        ].join("\n");
+        autoSnippet.push("# Load model directly", `from transformers import ${info.processor}, ${info.auto_model}`, "", `${processorVarName} = ${info.processor}.from_pretrained("${model.id}"` + remote_code_snippet + ")", `model = ${info.auto_model}.from_pretrained("${model.id}"` + remote_code_snippet + ")");
+        if (model.tags.includes("conversational")) {
+            if (model.tags.includes("image-text-to-text")) {
+                autoSnippet.push("messages = [", [
+                    "    {",
+                    '        "role": "user",',
+                    '        "content": [',
+                    '            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},',
+                    '            {"type": "text", "text": "What animal is on the candy?"}',
+                    "        ]",
+                    "    },",
+                ].join("\n"), "]");
+            }
+            else {
+                autoSnippet.push("messages = [", '    {"role": "user", "content": "Who are you?"},', "]");
+            }
+            autoSnippet.push("inputs = ${processorVarName}.apply_chat_template(", "	messages,", "	add_generation_prompt=True,", "	tokenize=True,", "	return_dict=True,", '	return_tensors="pt",', ").to(model.device)", "", "outputs = model.generate(**inputs, max_new_tokens=40)", 'print(${processorVarName}.decode(outputs[0][inputs["input_ids"].shape[-1]:]))');
+        }
     }
     else {
-        autoSnippet = [
-            "# Load model directly",
-            `from transformers import ${info.auto_model}`,
-            `model = ${info.auto_model}.from_pretrained("${model.id}"` + remote_code_snippet + ")",
-        ].join("\n");
+        autoSnippet.push("# Load model directly", `from transformers import ${info.auto_model}`, `model = ${info.auto_model}.from_pretrained("${model.id}"` + remote_code_snippet + ', torch_dtype="auto"),');
     }
@@ -1317,5 +1324,5 @@ if (model.pipeline_tag && LIBRARY_TASK_MAPPING.transformers?.includes(model.pipeline_tag)) {
         }
-        return [pipelineSnippet.join("\n"), autoSnippet];
+        return [pipelineSnippet.join("\n"), autoSnippet.join("\n")];
     }
-    return [autoSnippet];
+    return [autoSnippet.join("\n")];
 };
@@ -1322,0 +1329,0 @@ export const transformersJS = (model) => {

dist/esm/model-libraries.d.ts

@@ -521,2 +521,9 @@ import type { ModelData } from "./model-data.js";
     };
+    kronos: {
+        prettyLabel: string;
+        repoName: string;
+        repoUrl: string;
+        filter: false;
+        countDownloads: string;
+    };
     k2: {
@@ -1193,3 +1200,3 @@ prettyLabel: string;
 export declare const ALL_MODEL_LIBRARY_KEYS: ModelLibraryKey[];
-export declare const ALL_DISPLAY_MODEL_LIBRARY_KEYS: ("acestep" | "adapter-transformers" | "allennlp" | "anemoi" | "araclip" | "asteroid" | "audiocraft" | "audioseal" | "bagel-mot" | "ben2" | "bertopic" | "big_vision" | "birder" | "birefnet" | "bm25s" | "champ" | "chatterbox" | "chat_tts" | "colpali" | "comet" | "contexttab" | "cosmos" | "cxr-foundation" | "deepforest" | "depth-anything-v2" | "depth-pro" | "derm-foundation" | "describe-anything" | "dia-tts" | "diffree" | "diffusers" | "diffusionkit" | "doctr" | "cartesia_pytorch" | "cartesia_mlx" | "clipscope" | "cosyvoice" | "cotracker" | "edsnlp" | "elm" | "espnet" | "fairseq" | "fastai" | "fasttext" | "flair" | "fme" | "gemma.cpp" | "geometry-crafter" | "gliner" | "glyph-byt5" | "grok" | "hallo" | "hermes" | "hezar" | "htrflow" | "hunyuan-dit" | "hunyuan3d-2" | "imstoucan" | "index-tts" | "infinite-you" | "keras" | "tf-keras" | "keras-hub" | "kimi-audio" | "k2" | "lightning-ir" | "litert-lm" | "lerobot" | "liveportrait" | "llama-cpp-python" | "mini-omni2" | "mindspore" | "magi-1" | "magenta-realtime" | "mamba-ssm" | "mars5-tts" | "matanyone" | "mesh-anything" | "merlin" | "medvae" | "mitie" | "ml-agents" | "mlx" | "mlx-image" | "mlc-llm" | "model2vec" | "moshi" | "mtvcraft" | "nemo" | "open-oasis" | "open_clip" | "open-sora" | "outetts" | "paddlenlp" | "PaddleOCR" | "peft" | "perception-encoder" | "phantom-wan" | "pxia" | "pyannote-audio" | "py-feat" | "pythae" | "recurrentgemma" | "relik" | "refiners" | "renderformer" | "reverb" | "saelens" | "sam2" | "sample-factory" | "sapiens" | "seedvr" | "sentence-transformers" | "setfit" | "sklearn" | "spacy" | "span-marker" | "speechbrain" | "ssr-speech" | "stable-audio-tools" | "monkeyocr" | "diffusion-single-file" | "seed-story" | "soloaudio" | "stable-baselines3" | "stanza" | "swarmformer" | "f5-tts" | "genmo" | "tencent-song-generation" | "tensorflowtts" | "tabpfn" | "terratorch" | "tic-clip" | "timesfm" | "timm" | "tirex" | "torchgeo" | "transformers" | "transformers.js" | "trellis" | "ultralytics" | "univa" | "uni-3dar" | "unity-sentis" | "sana" | "videoprism" | "vfi-mamba" | "voicecraft" | "vui" | "wham" | "whisperkit" | "yolov10" | "zonos" | "3dtopia-xl")[];
+export declare const ALL_DISPLAY_MODEL_LIBRARY_KEYS: ("acestep" | "adapter-transformers" | "allennlp" | "anemoi" | "araclip" | "asteroid" | "audiocraft" | "audioseal" | "bagel-mot" | "ben2" | "bertopic" | "big_vision" | "birder" | "birefnet" | "bm25s" | "champ" | "chatterbox" | "chat_tts" | "colpali" | "comet" | "contexttab" | "cosmos" | "cxr-foundation" | "deepforest" | "depth-anything-v2" | "depth-pro" | "derm-foundation" | "describe-anything" | "dia-tts" | "diffree" | "diffusers" | "diffusionkit" | "doctr" | "cartesia_pytorch" | "cartesia_mlx" | "clipscope" | "cosyvoice" | "cotracker" | "edsnlp" | "elm" | "espnet" | "fairseq" | "fastai" | "fasttext" | "flair" | "fme" | "gemma.cpp" | "geometry-crafter" | "gliner" | "glyph-byt5" | "grok" | "hallo" | "hermes" | "hezar" | "htrflow" | "hunyuan-dit" | "hunyuan3d-2" | "imstoucan" | "index-tts" | "infinite-you" | "keras" | "tf-keras" | "keras-hub" | "kimi-audio" | "kronos" | "k2" | "lightning-ir" | "litert-lm" | "lerobot" | "liveportrait" | "llama-cpp-python" | "mini-omni2" | "mindspore" | "magi-1" | "magenta-realtime" | "mamba-ssm" | "mars5-tts" | "matanyone" | "mesh-anything" | "merlin" | "medvae" | "mitie" | "ml-agents" | "mlx" | "mlx-image" | "mlc-llm" | "model2vec" | "moshi" | "mtvcraft" | "nemo" | "open-oasis" | "open_clip" | "open-sora" | "outetts" | "paddlenlp" | "PaddleOCR" | "peft" | "perception-encoder" | "phantom-wan" | "pxia" | "pyannote-audio" | "py-feat" | "pythae" | "recurrentgemma" | "relik" | "refiners" | "renderformer" | "reverb" | "saelens" | "sam2" | "sample-factory" | "sapiens" | "seedvr" | "sentence-transformers" | "setfit" | "sklearn" | "spacy" | "span-marker" | "speechbrain" | "ssr-speech" | "stable-audio-tools" | "monkeyocr" | "diffusion-single-file" | "seed-story" | "soloaudio" | "stable-baselines3" | "stanza" | "swarmformer" | "f5-tts" | "genmo" | "tencent-song-generation" | "tensorflowtts" | "tabpfn" | "terratorch" | "tic-clip" | "timesfm" | "timm" | "tirex" | "torchgeo" | "transformers" | "transformers.js" | "trellis" | "ultralytics" | "univa" | "uni-3dar" | "unity-sentis" | "sana" | "videoprism" | "vfi-mamba" | "voicecraft" | "vui" | "wham" | "whisperkit" | "yolov10" | "zonos" | "3dtopia-xl")[];
 //# sourceMappingURL=model-libraries.d.ts.map

dist/esm/model-libraries.js

@@ -483,2 +483,9 @@ import * as snippets from "./model-libraries-snippets.js";
     },
+    kronos: {
+        prettyLabel: "KRONOS",
+        repoName: "KRONOS",
+        repoUrl: "https://github.com/mahmoodlab/KRONOS",
+        filter: false,
+        countDownloads: `path_extension:"pt"`,
+    },
     k2: {
@@ -485,0 +492,0 @@ prettyLabel: "K2",

package.json

 {
   "name": "@huggingface/tasks",
-  "version": "0.19.26",
+  "version": "0.19.27",
   "description": "List of ML tasks for huggingface.co/tasks",
@@ -5,0 +5,0 @@ "repository": "https://github.com/huggingface/huggingface.js.git",

src/model-libraries-snippets.ts

@@ -1376,5 +1376,5 @@ import type { ModelData } from "./model-data.js";
 
-	let autoSnippet: string;
+	const autoSnippet = [];
 	if (info.processor) {
-		const varName =
+		const processorVarName =
 			info.processor === "AutoTokenizer"
@@ -1385,15 +1385,46 @@ ? "tokenizer"
 				  : "processor";
-		autoSnippet = [
+		autoSnippet.push(
 			"# Load model directly",
 			`from transformers import ${info.processor}, ${info.auto_model}`,
 			"",
-			`${varName} = ${info.processor}.from_pretrained("${model.id}"` + remote_code_snippet + ")",
-			`model = ${info.auto_model}.from_pretrained("${model.id}"` + remote_code_snippet + ")",
-		].join("\n");
+			`${processorVarName} = ${info.processor}.from_pretrained("${model.id}"` + remote_code_snippet + ")",
+			`model = ${info.auto_model}.from_pretrained("${model.id}"` + remote_code_snippet + ")"
+		);
+		if (model.tags.includes("conversational")) {
+			if (model.tags.includes("image-text-to-text")) {
+				autoSnippet.push(
+					"messages = [",
+					[
+						"    {",
+						'        "role": "user",',
+						'        "content": [',
+						'            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},',
+						'            {"type": "text", "text": "What animal is on the candy?"}',
+						"        ]",
+						"    },",
+					].join("\n"),
+					"]"
+				);
+			} else {
+				autoSnippet.push("messages = [", '    {"role": "user", "content": "Who are you?"},', "]");
+			}
+			autoSnippet.push(
+				"inputs = ${processorVarName}.apply_chat_template(",
+				"	messages,",
+				"	add_generation_prompt=True,",
+				"	tokenize=True,",
+				"	return_dict=True,",
+				'	return_tensors="pt",',
+				").to(model.device)",
+				"",
+				"outputs = model.generate(**inputs, max_new_tokens=40)",
+				'print(${processorVarName}.decode(outputs[0][inputs["input_ids"].shape[-1]:]))'
+			);
+		}
 	} else {
-		autoSnippet = [
+		autoSnippet.push(
 			"# Load model directly",
 			`from transformers import ${info.auto_model}`,
-			`model = ${info.auto_model}.from_pretrained("${model.id}"` + remote_code_snippet + ")",
-		].join("\n");
+			`model = ${info.auto_model}.from_pretrained("${model.id}"` + remote_code_snippet + ', torch_dtype="auto"),'
+		);
 	}
@@ -1442,5 +1473,5 @@
 
-		return [pipelineSnippet.join("\n"), autoSnippet];
+		return [pipelineSnippet.join("\n"), autoSnippet.join("\n")];
 	}
-	return [autoSnippet];
+	return [autoSnippet.join("\n")];
 };
@@ -1447,0 +1478,0 @@

src/model-libraries.ts

@@ -527,2 +527,9 @@ import * as snippets from "./model-libraries-snippets.js";
 	},
+	kronos: {
+		prettyLabel: "KRONOS",
+		repoName: "KRONOS",
+		repoUrl: "https://github.com/mahmoodlab/KRONOS",
+		filter: false,
+		countDownloads: `path_extension:"pt"`,
+	},
 	k2: {
@@ -529,0 +536,0 @@ prettyLabel: "K2",

New alerts

URL strings

Supply chain risk

Package contains fragments of external URLs or IP addresses, which the package may be accessing at runtime.

Found 1 instance in 1 package

Fixed alerts

URL strings

Supply chain risk

Package contains fragments of external URLs or IP addresses, which the package may be accessing at runtime.

Found 1 instance in 1 package

Improved metrics

Total package byte prevSize

1904719

0.22%

Lines of code

47296

0.18%

No dependency changes