@huggingface/tasks - npm Package Compare versions

Comparing version 0.16.1 to 0.16.2

dist/commonjs/default-widget-inputs.js

@@ -93,5 +93,5 @@ "use strict";
             `Hi, what can you help me with?`,
-            `Hey, let's have a conversation!`,
-            `Hello there!`,
-            `Hey my name is Clara! How are you?`,
+            `What is 84 * 3 / 2?`,
+            `Tell me an interesting fact about the universe!`,
+            `Explain quantum computing in simple terms.`,
         ],
@@ -98,0 +98,0 @@ ],

dist/commonjs/hardware.d.ts

@@ -35,2 +35,6 @@ /**
         NVIDIA: {
+            H200: {
+                tflops: number;
+                memory: number[];
+            };
             H100: {
@@ -40,2 +44,6 @@ tflops: number;
             };
+            L40s: {
+                tflops: number;
+                memory: number[];
+            };
             L40: {
@@ -45,2 +53,10 @@ tflops: number;
             };
+            L20: {
+                tflops: number;
+                memory: number[];
+            };
+            L4: {
+                tflops: number;
+                memory: number[];
+            };
             "RTX 6000 Ada": {
@@ -102,2 +118,26 @@ tflops: number;
             };
+            "RTX 5090": {
+                tflops: number;
+                memory: number[];
+            };
+            "RTX 5090 D": {
+                tflops: number;
+                memory: number[];
+            };
+            "RTX 5080": {
+                tflops: number;
+                memory: number[];
+            };
+            "RTX 5080 Mobile": {
+                tflops: number;
+                memory: number[];
+            };
+            "RTX 5070": {
+                tflops: number;
+                memory: number[];
+            };
+            "RTX 5070 Mobile": {
+                tflops: number;
+                memory: number[];
+            };
             "RTX 4090": {
@@ -111,2 +151,6 @@ tflops: number;
             };
+            "RTX 4090 Mobile": {
+                tflops: number;
+                memory: number[];
+            };
             "RTX 4080 SUPER": {
@@ -120,2 +164,6 @@ tflops: number;
             };
+            "RTX 4080 Mobile": {
+                tflops: number;
+                memory: number[];
+            };
             "RTX 4070": {
@@ -125,2 +173,6 @@ tflops: number;
             };
+            "RTX 4070 Mobile": {
+                tflops: number;
+                memory: number[];
+            };
             "RTX 4070 Ti": {
@@ -146,2 +198,6 @@ tflops: number;
             };
+            "RTX 4060 Mobile": {
+                tflops: number;
+                memory: number[];
+            };
             "RTX 3090": {
@@ -163,2 +219,6 @@ tflops: number;
             };
+            "RTX 3080 Mobile": {
+                tflops: number;
+                memory: number[];
+            };
             "RTX 3070": {
@@ -172,3 +232,3 @@ tflops: number;
             };
-            "RTX 3070 Ti Laptop": {
+            "RTX 3070 Ti Mobile": {
                 tflops: number;
@@ -229,2 +289,6 @@ memory: number[];
             };
+            "GTX 1050 Ti": {
+                tflops: number;
+                memory: number[];
+            };
             "RTX Titan": {
@@ -258,2 +322,6 @@ tflops: number;
             };
+            P100: {
+                tflops: number;
+                memory: number[];
+            };
         };
@@ -260,0 +328,0 @@ AMD: {

dist/commonjs/hardware.js

@@ -20,2 +20,6 @@ "use strict";
         NVIDIA: {
+            H200: {
+                tflops: 241.3,
+                memory: [141],
+            },
             H100: {
@@ -25,2 +29,6 @@ tflops: 267.6,
             },
+            L40s: {
+                tflops: 91.61,
+                memory: [48],
+            },
             L40: {
@@ -30,2 +38,10 @@ tflops: 90.52,
             },
+            L20: {
+                tflops: 59.35,
+                memory: [48],
+            },
+            L4: {
+                tflops: 30.29,
+                memory: [24],
+            },
             "RTX 6000 Ada": {
@@ -87,2 +103,26 @@ tflops: 91.1,
             },
+            "RTX 5090": {
+                tflops: 104.8,
+                memory: [32],
+            },
+            "RTX 5090 D": {
+                tflops: 104.8,
+                memory: [32],
+            },
+            "RTX 5080": {
+                tflops: 56.28,
+                memory: [16],
+            },
+            "RTX 5080 Mobile": {
+                tflops: 24.58,
+                memory: [16],
+            },
+            "RTX 5070": {
+                tflops: 30.84,
+                memory: [12],
+            },
+            "RTX 5070 Mobile": {
+                tflops: 23.22,
+                memory: [8],
+            },
             "RTX 4090": {
@@ -96,2 +136,6 @@ tflops: 82.58,
             },
+            "RTX 4090 Mobile": {
+                tflops: 32.98,
+                memory: [16]
+            },
             "RTX 4080 SUPER": {
@@ -105,2 +149,6 @@ tflops: 52.2,
             },
+            "RTX 4080 Mobile": {
+                tflops: 24.72,
+                memory: [12]
+            },
             "RTX 4070": {
@@ -110,2 +158,6 @@ tflops: 29.15,
             },
+            "RTX 4070 Mobile": {
+                tflops: 15.62,
+                memory: [8]
+            },
             "RTX 4070 Ti": {
@@ -131,2 +183,6 @@ tflops: 40.09,
             },
+            "RTX 4060 Mobile": {
+                tflops: 11.61,
+                memory: [8]
+            },
             "RTX 3090": {
@@ -148,2 +204,6 @@ tflops: 35.58,
             },
+            "RTX 3080 Mobile": {
+                tflops: 18.98,
+                memory: [8]
+            },
             "RTX 3070": {
@@ -157,3 +217,3 @@ tflops: 20.31,
             },
-            "RTX 3070 Ti Laptop": {
+            "RTX 3070 Ti Mobile": {
                 tflops: 16.6,
@@ -214,2 +274,6 @@ memory: [8],
             },
+            "GTX 1050 Ti": {
+                tflops: 2.1, // float32 (GPU does not support native float16)
+                memory: [4]
+            },
             "RTX Titan": {
@@ -243,2 +307,6 @@ tflops: 32.62,
             },
+            P100: {
+                tflops: 19.05,
+                memory: [16],
+            },
         },
@@ -245,0 +313,0 @@ AMD: {

dist/commonjs/local-apps.js

@@ -74,14 +74,15 @@ "use strict";
 const snippetNodeLlamaCppCli = (model, filepath) => {
+    let tagName = "{{OLLAMA_TAG}}";
+    if (filepath) {
+        const quantLabel = (0, gguf_js_1.parseGGUFQuantLabel)(filepath);
+        tagName = quantLabel ? `:${quantLabel}` : tagName;
+    }
     return [
         {
             title: "Chat with the model",
-            content: [
-                `npx -y node-llama-cpp chat \\`,
-                `  --model "hf:${model.id}/${filepath ?? "{{GGUF_FILE}}"}" \\`,
-                `  --prompt 'Hi there!'`,
-            ].join("\n"),
+            content: `npx -y node-llama-cpp chat hf:${model.id}${tagName}`,
         },
         {
             title: "Estimate the model compatibility with your hardware",
-            content: `npx -y node-llama-cpp inspect estimate "hf:${model.id}/${filepath ?? "{{GGUF_FILE}}"}"`,
+            content: `npx -y node-llama-cpp inspect estimate hf:${model.id}${tagName}`,
         },
@@ -88,0 +89,0 @@ ];

dist/commonjs/model-libraries-snippets.js

@@ -104,17 +104,10 @@ "use strict";
 const cxr_foundation = () => [
-    `!git clone https://github.com/Google-Health/cxr-foundation.git
-import tensorflow as tf, sys, requests
-sys.path.append('cxr-foundation/python/')
+    `# pip install git+https://github.com/Google-Health/cxr-foundation.git#subdirectory=python
 
-# Install dependencies
-major_version = tf.__version__.rsplit(".", 1)[0]
-!pip install tensorflow-text=={major_version} pypng && pip install --no-deps pydicom hcls_imaging_ml_toolkit retrying
-
-# Load image (Stillwaterising, CC0, via Wikimedia Commons)
+# Load image as grayscale (Stillwaterising, CC0, via Wikimedia Commons)
+import requests
 from PIL import Image
 from io import BytesIO
 image_url = "https://upload.wikimedia.org/wikipedia/commons/c/c8/Chest_Xray_PA_3-8-2010.png"
-response = requests.get(image_url, headers={'User-Agent': 'Demo'}, stream=True)
-response.raw.decode_content = True # Ensure correct decoding
-img = Image.open(BytesIO(response.content)).convert('L') # Convert to grayscale
+img = Image.open(requests.get(image_url, headers={'User-Agent': 'Demo'}, stream=True).raw).convert('L')
 
@@ -121,0 +114,0 @@ # Run inference

dist/commonjs/model-libraries.d.ts

@@ -172,2 +172,8 @@ import type { ModelData } from "./model-data.js";
     };
+    comet: {
+        prettyLabel: string;
+        repoName: string;
+        repoUrl: string;
+        countDownloads: string;
+    };
     cosmos: {
@@ -905,3 +911,3 @@ prettyLabel: string;
 export declare const ALL_MODEL_LIBRARY_KEYS: ModelLibraryKey[];
-export declare const ALL_DISPLAY_MODEL_LIBRARY_KEYS: ("adapter-transformers" | "allennlp" | "anemoi" | "asteroid" | "audiocraft" | "audioseal" | "ben2" | "bertopic" | "big_vision" | "birder" | "birefnet" | "bm25s" | "champ" | "chat_tts" | "colpali" | "cosmos" | "cxr-foundation" | "deepforest" | "depth-anything-v2" | "depth-pro" | "derm-foundation" | "diffree" | "diffusers" | "diffusionkit" | "doctr" | "cartesia_pytorch" | "cartesia_mlx" | "clipscope" | "cosyvoice" | "cotracker" | "edsnlp" | "elm" | "espnet" | "fairseq" | "fastai" | "fasttext" | "flair" | "gemma.cpp" | "gliner" | "glyph-byt5" | "grok" | "hallo" | "hezar" | "htrflow" | "hunyuan-dit" | "imstoucan" | "keras" | "tf-keras" | "keras-hub" | "k2" | "liveportrait" | "llama-cpp-python" | "mini-omni2" | "mindspore" | "mamba-ssm" | "mars5-tts" | "mesh-anything" | "mitie" | "ml-agents" | "mlx" | "mlx-image" | "mlc-llm" | "model2vec" | "moshi" | "nemo" | "open-oasis" | "open_clip" | "paddlenlp" | "peft" | "pxia" | "pyannote-audio" | "py-feat" | "pythae" | "recurrentgemma" | "relik" | "refiners" | "reverb" | "saelens" | "sam2" | "sample-factory" | "sapiens" | "sentence-transformers" | "setfit" | "sklearn" | "spacy" | "span-marker" | "speechbrain" | "ssr-speech" | "stable-audio-tools" | "diffusion-single-file" | "seed-story" | "soloaudio" | "stable-baselines3" | "stanza" | "swarmformer" | "f5-tts" | "genmo" | "tensorflowtts" | "tabpfn" | "terratorch" | "tic-clip" | "timesfm" | "timm" | "transformers" | "transformers.js" | "trellis" | "ultralytics" | "unity-sentis" | "sana" | "vfi-mamba" | "voicecraft" | "whisperkit" | "yolov10" | "3dtopia-xl")[];
+export declare const ALL_DISPLAY_MODEL_LIBRARY_KEYS: ("adapter-transformers" | "allennlp" | "anemoi" | "asteroid" | "audiocraft" | "audioseal" | "ben2" | "bertopic" | "big_vision" | "birder" | "birefnet" | "bm25s" | "champ" | "chat_tts" | "colpali" | "comet" | "cosmos" | "cxr-foundation" | "deepforest" | "depth-anything-v2" | "depth-pro" | "derm-foundation" | "diffree" | "diffusers" | "diffusionkit" | "doctr" | "cartesia_pytorch" | "cartesia_mlx" | "clipscope" | "cosyvoice" | "cotracker" | "edsnlp" | "elm" | "espnet" | "fairseq" | "fastai" | "fasttext" | "flair" | "gemma.cpp" | "gliner" | "glyph-byt5" | "grok" | "hallo" | "hezar" | "htrflow" | "hunyuan-dit" | "imstoucan" | "keras" | "tf-keras" | "keras-hub" | "k2" | "liveportrait" | "llama-cpp-python" | "mini-omni2" | "mindspore" | "mamba-ssm" | "mars5-tts" | "mesh-anything" | "mitie" | "ml-agents" | "mlx" | "mlx-image" | "mlc-llm" | "model2vec" | "moshi" | "nemo" | "open-oasis" | "open_clip" | "paddlenlp" | "peft" | "pxia" | "pyannote-audio" | "py-feat" | "pythae" | "recurrentgemma" | "relik" | "refiners" | "reverb" | "saelens" | "sam2" | "sample-factory" | "sapiens" | "sentence-transformers" | "setfit" | "sklearn" | "spacy" | "span-marker" | "speechbrain" | "ssr-speech" | "stable-audio-tools" | "diffusion-single-file" | "seed-story" | "soloaudio" | "stable-baselines3" | "stanza" | "swarmformer" | "f5-tts" | "genmo" | "tensorflowtts" | "tabpfn" | "terratorch" | "tic-clip" | "timesfm" | "timm" | "transformers" | "transformers.js" | "trellis" | "ultralytics" | "unity-sentis" | "sana" | "vfi-mamba" | "voicecraft" | "whisperkit" | "yolov10" | "3dtopia-xl")[];
 //# sourceMappingURL=model-libraries.d.ts.map

dist/commonjs/model-libraries.js

@@ -158,2 +158,8 @@ "use strict";
     },
+    comet: {
+        prettyLabel: "COMET",
+        repoName: "COMET",
+        repoUrl: "https://github.com/Unbabel/COMET/",
+        countDownloads: `path:"hparams.yaml"`,
+    },
     cosmos: {
@@ -160,0 +166,0 @@ prettyLabel: "Cosmos",

dist/esm/default-widget-inputs.js

@@ -90,5 +90,5 @@ /// NOTE TO CONTRIBUTORS:
             `Hi, what can you help me with?`,
-            `Hey, let's have a conversation!`,
-            `Hello there!`,
-            `Hey my name is Clara! How are you?`,
+            `What is 84 * 3 / 2?`,
+            `Tell me an interesting fact about the universe!`,
+            `Explain quantum computing in simple terms.`,
         ],
@@ -95,0 +95,0 @@ ],

dist/esm/hardware.d.ts

@@ -35,2 +35,6 @@ /**
         NVIDIA: {
+            H200: {
+                tflops: number;
+                memory: number[];
+            };
             H100: {
@@ -40,2 +44,6 @@ tflops: number;
             };
+            L40s: {
+                tflops: number;
+                memory: number[];
+            };
             L40: {
@@ -45,2 +53,10 @@ tflops: number;
             };
+            L20: {
+                tflops: number;
+                memory: number[];
+            };
+            L4: {
+                tflops: number;
+                memory: number[];
+            };
             "RTX 6000 Ada": {
@@ -102,2 +118,26 @@ tflops: number;
             };
+            "RTX 5090": {
+                tflops: number;
+                memory: number[];
+            };
+            "RTX 5090 D": {
+                tflops: number;
+                memory: number[];
+            };
+            "RTX 5080": {
+                tflops: number;
+                memory: number[];
+            };
+            "RTX 5080 Mobile": {
+                tflops: number;
+                memory: number[];
+            };
+            "RTX 5070": {
+                tflops: number;
+                memory: number[];
+            };
+            "RTX 5070 Mobile": {
+                tflops: number;
+                memory: number[];
+            };
             "RTX 4090": {
@@ -111,2 +151,6 @@ tflops: number;
             };
+            "RTX 4090 Mobile": {
+                tflops: number;
+                memory: number[];
+            };
             "RTX 4080 SUPER": {
@@ -120,2 +164,6 @@ tflops: number;
             };
+            "RTX 4080 Mobile": {
+                tflops: number;
+                memory: number[];
+            };
             "RTX 4070": {
@@ -125,2 +173,6 @@ tflops: number;
             };
+            "RTX 4070 Mobile": {
+                tflops: number;
+                memory: number[];
+            };
             "RTX 4070 Ti": {
@@ -146,2 +198,6 @@ tflops: number;
             };
+            "RTX 4060 Mobile": {
+                tflops: number;
+                memory: number[];
+            };
             "RTX 3090": {
@@ -163,2 +219,6 @@ tflops: number;
             };
+            "RTX 3080 Mobile": {
+                tflops: number;
+                memory: number[];
+            };
             "RTX 3070": {
@@ -172,3 +232,3 @@ tflops: number;
             };
-            "RTX 3070 Ti Laptop": {
+            "RTX 3070 Ti Mobile": {
                 tflops: number;
@@ -229,2 +289,6 @@ memory: number[];
             };
+            "GTX 1050 Ti": {
+                tflops: number;
+                memory: number[];
+            };
             "RTX Titan": {
@@ -258,2 +322,6 @@ tflops: number;
             };
+            P100: {
+                tflops: number;
+                memory: number[];
+            };
         };
@@ -260,0 +328,0 @@ AMD: {

dist/esm/hardware.js

@@ -17,2 +17,6 @@ /**
         NVIDIA: {
+            H200: {
+                tflops: 241.3,
+                memory: [141],
+            },
             H100: {
@@ -22,2 +26,6 @@ tflops: 267.6,
             },
+            L40s: {
+                tflops: 91.61,
+                memory: [48],
+            },
             L40: {
@@ -27,2 +35,10 @@ tflops: 90.52,
             },
+            L20: {
+                tflops: 59.35,
+                memory: [48],
+            },
+            L4: {
+                tflops: 30.29,
+                memory: [24],
+            },
             "RTX 6000 Ada": {
@@ -84,2 +100,26 @@ tflops: 91.1,
             },
+            "RTX 5090": {
+                tflops: 104.8,
+                memory: [32],
+            },
+            "RTX 5090 D": {
+                tflops: 104.8,
+                memory: [32],
+            },
+            "RTX 5080": {
+                tflops: 56.28,
+                memory: [16],
+            },
+            "RTX 5080 Mobile": {
+                tflops: 24.58,
+                memory: [16],
+            },
+            "RTX 5070": {
+                tflops: 30.84,
+                memory: [12],
+            },
+            "RTX 5070 Mobile": {
+                tflops: 23.22,
+                memory: [8],
+            },
             "RTX 4090": {
@@ -93,2 +133,6 @@ tflops: 82.58,
             },
+            "RTX 4090 Mobile": {
+                tflops: 32.98,
+                memory: [16]
+            },
             "RTX 4080 SUPER": {
@@ -102,2 +146,6 @@ tflops: 52.2,
             },
+            "RTX 4080 Mobile": {
+                tflops: 24.72,
+                memory: [12]
+            },
             "RTX 4070": {
@@ -107,2 +155,6 @@ tflops: 29.15,
             },
+            "RTX 4070 Mobile": {
+                tflops: 15.62,
+                memory: [8]
+            },
             "RTX 4070 Ti": {
@@ -128,2 +180,6 @@ tflops: 40.09,
             },
+            "RTX 4060 Mobile": {
+                tflops: 11.61,
+                memory: [8]
+            },
             "RTX 3090": {
@@ -145,2 +201,6 @@ tflops: 35.58,
             },
+            "RTX 3080 Mobile": {
+                tflops: 18.98,
+                memory: [8]
+            },
             "RTX 3070": {
@@ -154,3 +214,3 @@ tflops: 20.31,
             },
-            "RTX 3070 Ti Laptop": {
+            "RTX 3070 Ti Mobile": {
                 tflops: 16.6,
@@ -211,2 +271,6 @@ memory: [8],
             },
+            "GTX 1050 Ti": {
+                tflops: 2.1, // float32 (GPU does not support native float16)
+                memory: [4]
+            },
             "RTX Titan": {
@@ -240,2 +304,6 @@ tflops: 32.62,
             },
+            P100: {
+                tflops: 19.05,
+                memory: [16],
+            },
         },
@@ -242,0 +310,0 @@ AMD: {

dist/esm/local-apps.js

@@ -71,14 +71,15 @@ import { parseGGUFQuantLabel } from "./gguf.js";
 const snippetNodeLlamaCppCli = (model, filepath) => {
+    let tagName = "{{OLLAMA_TAG}}";
+    if (filepath) {
+        const quantLabel = parseGGUFQuantLabel(filepath);
+        tagName = quantLabel ? `:${quantLabel}` : tagName;
+    }
     return [
         {
             title: "Chat with the model",
-            content: [
-                `npx -y node-llama-cpp chat \\`,
-                `  --model "hf:${model.id}/${filepath ?? "{{GGUF_FILE}}"}" \\`,
-                `  --prompt 'Hi there!'`,
-            ].join("\n"),
+            content: `npx -y node-llama-cpp chat hf:${model.id}${tagName}`,
         },
         {
             title: "Estimate the model compatibility with your hardware",
-            content: `npx -y node-llama-cpp inspect estimate "hf:${model.id}/${filepath ?? "{{GGUF_FILE}}"}"`,
+            content: `npx -y node-llama-cpp inspect estimate hf:${model.id}${tagName}`,
         },
@@ -85,0 +86,0 @@ ];

dist/esm/model-libraries-snippets.js

@@ -93,17 +93,10 @@ import { LIBRARY_TASK_MAPPING } from "./library-to-tasks.js";
 export const cxr_foundation = () => [
-    `!git clone https://github.com/Google-Health/cxr-foundation.git
-import tensorflow as tf, sys, requests
-sys.path.append('cxr-foundation/python/')
+    `# pip install git+https://github.com/Google-Health/cxr-foundation.git#subdirectory=python
 
-# Install dependencies
-major_version = tf.__version__.rsplit(".", 1)[0]
-!pip install tensorflow-text=={major_version} pypng && pip install --no-deps pydicom hcls_imaging_ml_toolkit retrying
-
-# Load image (Stillwaterising, CC0, via Wikimedia Commons)
+# Load image as grayscale (Stillwaterising, CC0, via Wikimedia Commons)
+import requests
 from PIL import Image
 from io import BytesIO
 image_url = "https://upload.wikimedia.org/wikipedia/commons/c/c8/Chest_Xray_PA_3-8-2010.png"
-response = requests.get(image_url, headers={'User-Agent': 'Demo'}, stream=True)
-response.raw.decode_content = True # Ensure correct decoding
-img = Image.open(BytesIO(response.content)).convert('L') # Convert to grayscale
+img = Image.open(requests.get(image_url, headers={'User-Agent': 'Demo'}, stream=True).raw).convert('L')
 
@@ -110,0 +103,0 @@ # Run inference

dist/esm/model-libraries.d.ts

@@ -172,2 +172,8 @@ import type { ModelData } from "./model-data.js";
     };
+    comet: {
+        prettyLabel: string;
+        repoName: string;
+        repoUrl: string;
+        countDownloads: string;
+    };
     cosmos: {
@@ -905,3 +911,3 @@ prettyLabel: string;
 export declare const ALL_MODEL_LIBRARY_KEYS: ModelLibraryKey[];
-export declare const ALL_DISPLAY_MODEL_LIBRARY_KEYS: ("adapter-transformers" | "allennlp" | "anemoi" | "asteroid" | "audiocraft" | "audioseal" | "ben2" | "bertopic" | "big_vision" | "birder" | "birefnet" | "bm25s" | "champ" | "chat_tts" | "colpali" | "cosmos" | "cxr-foundation" | "deepforest" | "depth-anything-v2" | "depth-pro" | "derm-foundation" | "diffree" | "diffusers" | "diffusionkit" | "doctr" | "cartesia_pytorch" | "cartesia_mlx" | "clipscope" | "cosyvoice" | "cotracker" | "edsnlp" | "elm" | "espnet" | "fairseq" | "fastai" | "fasttext" | "flair" | "gemma.cpp" | "gliner" | "glyph-byt5" | "grok" | "hallo" | "hezar" | "htrflow" | "hunyuan-dit" | "imstoucan" | "keras" | "tf-keras" | "keras-hub" | "k2" | "liveportrait" | "llama-cpp-python" | "mini-omni2" | "mindspore" | "mamba-ssm" | "mars5-tts" | "mesh-anything" | "mitie" | "ml-agents" | "mlx" | "mlx-image" | "mlc-llm" | "model2vec" | "moshi" | "nemo" | "open-oasis" | "open_clip" | "paddlenlp" | "peft" | "pxia" | "pyannote-audio" | "py-feat" | "pythae" | "recurrentgemma" | "relik" | "refiners" | "reverb" | "saelens" | "sam2" | "sample-factory" | "sapiens" | "sentence-transformers" | "setfit" | "sklearn" | "spacy" | "span-marker" | "speechbrain" | "ssr-speech" | "stable-audio-tools" | "diffusion-single-file" | "seed-story" | "soloaudio" | "stable-baselines3" | "stanza" | "swarmformer" | "f5-tts" | "genmo" | "tensorflowtts" | "tabpfn" | "terratorch" | "tic-clip" | "timesfm" | "timm" | "transformers" | "transformers.js" | "trellis" | "ultralytics" | "unity-sentis" | "sana" | "vfi-mamba" | "voicecraft" | "whisperkit" | "yolov10" | "3dtopia-xl")[];
+export declare const ALL_DISPLAY_MODEL_LIBRARY_KEYS: ("adapter-transformers" | "allennlp" | "anemoi" | "asteroid" | "audiocraft" | "audioseal" | "ben2" | "bertopic" | "big_vision" | "birder" | "birefnet" | "bm25s" | "champ" | "chat_tts" | "colpali" | "comet" | "cosmos" | "cxr-foundation" | "deepforest" | "depth-anything-v2" | "depth-pro" | "derm-foundation" | "diffree" | "diffusers" | "diffusionkit" | "doctr" | "cartesia_pytorch" | "cartesia_mlx" | "clipscope" | "cosyvoice" | "cotracker" | "edsnlp" | "elm" | "espnet" | "fairseq" | "fastai" | "fasttext" | "flair" | "gemma.cpp" | "gliner" | "glyph-byt5" | "grok" | "hallo" | "hezar" | "htrflow" | "hunyuan-dit" | "imstoucan" | "keras" | "tf-keras" | "keras-hub" | "k2" | "liveportrait" | "llama-cpp-python" | "mini-omni2" | "mindspore" | "mamba-ssm" | "mars5-tts" | "mesh-anything" | "mitie" | "ml-agents" | "mlx" | "mlx-image" | "mlc-llm" | "model2vec" | "moshi" | "nemo" | "open-oasis" | "open_clip" | "paddlenlp" | "peft" | "pxia" | "pyannote-audio" | "py-feat" | "pythae" | "recurrentgemma" | "relik" | "refiners" | "reverb" | "saelens" | "sam2" | "sample-factory" | "sapiens" | "sentence-transformers" | "setfit" | "sklearn" | "spacy" | "span-marker" | "speechbrain" | "ssr-speech" | "stable-audio-tools" | "diffusion-single-file" | "seed-story" | "soloaudio" | "stable-baselines3" | "stanza" | "swarmformer" | "f5-tts" | "genmo" | "tensorflowtts" | "tabpfn" | "terratorch" | "tic-clip" | "timesfm" | "timm" | "transformers" | "transformers.js" | "trellis" | "ultralytics" | "unity-sentis" | "sana" | "vfi-mamba" | "voicecraft" | "whisperkit" | "yolov10" | "3dtopia-xl")[];
 //# sourceMappingURL=model-libraries.d.ts.map

dist/esm/model-libraries.js

@@ -132,2 +132,8 @@ import * as snippets from "./model-libraries-snippets.js";
     },
+    comet: {
+        prettyLabel: "COMET",
+        repoName: "COMET",
+        repoUrl: "https://github.com/Unbabel/COMET/",
+        countDownloads: `path:"hparams.yaml"`,
+    },
     cosmos: {
@@ -134,0 +140,0 @@ prettyLabel: "Cosmos",

dist/esm/snippets/python.js

@@ -1,2 +0,2 @@
-import { openAIbaseUrl, } from "../inference-providers.js";
+import { openAIbaseUrl } from "../inference-providers.js";
 import { stringifyGenerationConfig, stringifyMessages } from "./common.js";
@@ -3,0 +3,0 @@ import { getModelInputSnippet } from "./inputs.js";

package.json

 {
   "name": "@huggingface/tasks",
   "packageManager": "pnpm@8.10.5",
-  "version": "0.16.1",
+  "version": "0.16.2",
   "description": "List of ML tasks for huggingface.co/tasks",
@@ -6,0 +6,0 @@ "repository": "https://github.com/huggingface/huggingface.js.git",

src/default-widget-inputs.ts

@@ -99,5 +99,5 @@ import type { WidgetExample } from "./widget-example.js";
 			`Hi, what can you help me with?`,
-			`Hey, let's have a conversation!`,
-			`Hello there!`,
-			`Hey my name is Clara! How are you?`,
+			`What is 84 * 3 / 2?`,
+			`Tell me an interesting fact about the universe!`,
+			`Explain quantum computing in simple terms.`,
 		],
@@ -104,0 +104,0 @@ ],

src/hardware.ts

@@ -39,2 +39,6 @@ /**
 		NVIDIA: {
+			H200: {
+				tflops: 241.3,
+				memory: [141],
+			},
 			H100: {
@@ -44,2 +48,6 @@ tflops: 267.6,
 			},
+			L40s: {
+				tflops: 91.61,
+				memory: [48],
+			},
 			L40: {
@@ -49,2 +57,10 @@ tflops: 90.52,
 			},
+			L20: {
+				tflops: 59.35,
+				memory: [48],
+			},
+			L4: {
+				tflops: 30.29,
+				memory: [24],
+			},
 			"RTX 6000 Ada": {
@@ -106,2 +122,26 @@ tflops: 91.1,
 			},
+			"RTX 5090": {
+				tflops: 104.8,
+				memory: [32],
+			},
+			"RTX 5090 D": {
+				tflops: 104.8,
+				memory: [32],
+			},
+			"RTX 5080": {
+				tflops: 56.28,
+				memory: [16],
+			},
+			"RTX 5080 Mobile": {
+				tflops: 24.58,
+				memory: [16],
+			},
+			"RTX 5070": {
+				tflops: 30.84,
+				memory: [12],
+			},
+			"RTX 5070 Mobile": {
+				tflops: 23.22,
+				memory: [8],
+			},
 			"RTX 4090": {
@@ -115,2 +155,6 @@ tflops: 82.58,
 			},
+			"RTX 4090 Mobile": {
+				tflops: 32.98,
+				memory: [16]
+			},
 			"RTX 4080 SUPER": {
@@ -124,2 +168,6 @@ tflops: 52.2,
 			},
+			"RTX 4080 Mobile": {
+				tflops: 24.72,
+				memory: [12]
+			},
 			"RTX 4070": {
@@ -129,2 +177,6 @@ tflops: 29.15,
 			},
+			"RTX 4070 Mobile": {
+				tflops: 15.62,
+				memory: [8]
+			},
 			"RTX 4070 Ti": {
@@ -150,2 +202,6 @@ tflops: 40.09,
 			},
+			"RTX 4060 Mobile": {
+				tflops: 11.61,
+				memory: [8]
+			},
 			"RTX 3090": {
@@ -167,2 +223,6 @@ tflops: 35.58,
 			},
+			"RTX 3080 Mobile": {
+				tflops: 18.98,
+				memory: [8]
+			},
 			"RTX 3070": {
@@ -176,3 +236,3 @@ tflops: 20.31,
 			},
-			"RTX 3070 Ti Laptop": {
+			"RTX 3070 Ti Mobile": {
 				tflops: 16.6,
@@ -233,2 +293,6 @@ memory: [8],
 			},
+			"GTX 1050 Ti": {
+				tflops: 2.1, // float32 (GPU does not support native float16)
+				memory: [4]
+			},
 			"RTX Titan": {
@@ -262,2 +326,6 @@ tflops: 32.62,
 			},
+			P100: {
+				tflops: 19.05,
+				memory: [16],
+			},
 		},
@@ -264,0 +332,0 @@ AMD: {

src/local-apps.ts

@@ -141,14 +141,17 @@ import { parseGGUFQuantLabel } from "./gguf.js";
 const snippetNodeLlamaCppCli = (model: ModelData, filepath?: string): LocalAppSnippet[] => {
+	let tagName = "{{OLLAMA_TAG}}";
+
+	if (filepath) {
+		const quantLabel = parseGGUFQuantLabel(filepath);
+		tagName = quantLabel ? `:${quantLabel}` : tagName;
+	}
+
 	return [
 		{
 			title: "Chat with the model",
-			content: [
-				`npx -y node-llama-cpp chat \\`,
-				`  --model "hf:${model.id}/${filepath ?? "{{GGUF_FILE}}"}" \\`,
-				`  --prompt 'Hi there!'`,
-			].join("\n"),
+			content: `npx -y node-llama-cpp chat hf:${model.id}${tagName}`,
 		},
 		{
 			title: "Estimate the model compatibility with your hardware",
-			content: `npx -y node-llama-cpp inspect estimate "hf:${model.id}/${filepath ?? "{{GGUF_FILE}}"}"`,
+			content: `npx -y node-llama-cpp inspect estimate hf:${model.id}${tagName}`,
 		},
@@ -155,0 +158,0 @@ ];

src/model-libraries-snippets.ts

@@ -113,17 +113,10 @@ import type { ModelData } from "./model-data.js";
 export const cxr_foundation = (): string[] => [
-	`!git clone https://github.com/Google-Health/cxr-foundation.git
-import tensorflow as tf, sys, requests
-sys.path.append('cxr-foundation/python/')
+	`# pip install git+https://github.com/Google-Health/cxr-foundation.git#subdirectory=python
 
-# Install dependencies
-major_version = tf.__version__.rsplit(".", 1)[0]
-!pip install tensorflow-text=={major_version} pypng && pip install --no-deps pydicom hcls_imaging_ml_toolkit retrying
-
-# Load image (Stillwaterising, CC0, via Wikimedia Commons)
+# Load image as grayscale (Stillwaterising, CC0, via Wikimedia Commons)
+import requests
 from PIL import Image
 from io import BytesIO
 image_url = "https://upload.wikimedia.org/wikipedia/commons/c/c8/Chest_Xray_PA_3-8-2010.png"
-response = requests.get(image_url, headers={'User-Agent': 'Demo'}, stream=True)
-response.raw.decode_content = True # Ensure correct decoding
-img = Image.open(BytesIO(response.content)).convert('L') # Convert to grayscale
+img = Image.open(requests.get(image_url, headers={'User-Agent': 'Demo'}, stream=True).raw).convert('L')
 
@@ -130,0 +123,0 @@ # Run inference

src/model-libraries.ts

@@ -176,2 +176,8 @@ import * as snippets from "./model-libraries-snippets.js";
 	},
+	comet: {
+		prettyLabel: "COMET",
+		repoName: "COMET",
+		repoUrl: "https://github.com/Unbabel/COMET/",
+		countDownloads: `path:"hparams.yaml"`,
+	},
 	cosmos: {
@@ -178,0 +184,0 @@ prettyLabel: "Cosmos",

src/snippets/js.ts

@@ -30,5 +30,5 @@ import { openAIbaseUrl, type SnippetInferenceProvider } from "../inference-providers.js";
 			? [
-				{
-					client: "huggingface.js",
-					content: `\
+					{
+						client: "huggingface.js",
+						content: `\
 import { HfInference } from "@huggingface/inference";
@@ -46,4 +46,4 @@
 `,
-				},
-			]
+					},
+			  ]
 			: []),
@@ -222,4 +222,4 @@ {
 		query({"inputs": ${getModelInputSnippet(
-				model
-			)}, "parameters": {"candidate_labels": ["refund", "legal", "faq"]}}).then((response) => {
+			model
+		)}, "parameters": {"candidate_labels": ["refund", "legal", "faq"]}}).then((response) => {
 			console.log(JSON.stringify(response));
@@ -255,5 +255,5 @@ });`,
 			? [
-				{
-					client: "fetch",
-					content: `async function query(data) {
+					{
+						client: "fetch",
+						content: `async function query(data) {
 	const response = await fetch(
@@ -276,4 +276,4 @@ "https://router.huggingface.co/hf-inference/models/${model.id}",
 });`,
-				},
-			]
+					},
+			  ]
 			: []),
@@ -280,0 +280,0 @@ ];

src/snippets/python.ts

@@ -1,5 +0,2 @@
-import {
-	openAIbaseUrl,
-	type SnippetInferenceProvider,
-} from "../inference-providers.js";
+import { openAIbaseUrl, type SnippetInferenceProvider } from "../inference-providers.js";
 import type { PipelineType, WidgetType } from "../pipelines.js";
@@ -209,5 +206,5 @@ import type { ChatCompletionInputMessage, GenerationParameters } from "../tasks/index.js";
 			? [
-				{
-					client: "huggingface_hub",
-					content: `\
+					{
+						client: "huggingface_hub",
+						content: `\
 ${snippetImportInferenceClient(accessToken, provider)}
@@ -223,4 +220,4 @@
 `,
-				},
-			]
+					},
+			  ]
 			: []),
@@ -261,3 +258,3 @@ {
 	provider: SnippetInferenceProvider,
-	providerModelId?: string,
+	providerModelId?: string
 ): InferenceSnippet[] => {
@@ -278,5 +275,5 @@ return [
 			? [
-				{
-					client: "fal-client",
-					content: `\
+					{
+						client: "fal-client",
+						content: `\
 import fal_client
@@ -292,10 +289,10 @@
 `,
-				},
-			]
+					},
+			  ]
 			: []),
 		...(provider === "hf-inference"
 			? [
-				{
-					client: "requests",
-					content: `\
+					{
+						client: "requests",
+						content: `\
 def query(payload):
@@ -313,4 +310,4 @@ response = requests.post(API_URL, headers=headers, json=payload)
 image = Image.open(io.BytesIO(image_bytes))`,
-				},
-			]
+					},
+			  ]
 			: []),
@@ -317,0 +314,0 @@ ];

No alert changes

Improved metrics

Total package byte prevSize

1787723

increased by0.48%

Lines of code

44542

increased by0.8%

No dependency changes