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.gitattributes

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 # Video files - compressed
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latentscope/.gitattributes

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latentscope/embeddings/embedding-002.h5

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latentscope/embeddings/embedding-002.json

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latentscope/jobs/2b037506-b264-4221-a686-ff520c7a3cfa.json

@@ -0,0 +1 @@
+{"id": "2b037506-b264-4221-a686-ff520c7a3cfa", "dataset": "ls-common-corpus-100k", "job_name": "umap", "command": "ls-umap \"ls-common-corpus-100k\" \"embedding-002\" 25 0.1 --seed=42", "status": "completed", "last_update": "2025-01-23 12:12:28.068592", "progress": ["Loading environment variables from: /Users/enjalot/code/latent-scope/.env", "RUNNING: umap-002", "loading embeddings", "Loading environment variables from: /Users/enjalot/code/latent-scope/.env", "reducing 768 embeddings to 2 dimensions", "/Users/enjalot/code/latent-scope/testenv/lib/python3.12/site-packages/umap/umap_.py:1945: UserWarning: n_jobs value 1 overridden to 1 by setting random_state. Use no seed for parallelism.", "warn(f\"n_jobs value {self.n_jobs} overridden to 1 by setting random_state. Use no seed for parallelism.\")", "UMAP(angular_rp_forest=True, metric='cosine', n_jobs=1, n_neighbors=25, random_state=42, verbose=True)", "Thu Jan 23 12:10:51 2025 Construct fuzzy simplicial set", "Thu Jan 23 12:10:51 2025 Finding Nearest Neighbors", "Thu Jan 23 12:10:51 2025 Building RP forest with 21 trees", "Thu Jan 23 12:10:58 2025 NN descent for 17 iterations", "1  /  17", "2  /  17", "3  /  17", "4  /  17", "5  /  17", "6  /  17", "Stopping threshold met -- exiting after 6 iterations", "Thu Jan 23 12:11:33 2025 Finished Nearest Neighbor Search", "Thu Jan 23 12:11:34 2025 Construct embedding", "", "Epochs completed:   0%|            0/200 [00:00]\tcompleted  0  /  200 epochs", "", "Epochs completed:   0%|            1/200 [00:00]", "Epochs completed:   2%| \u258f          3/200 [00:00]", "Epochs completed:   2%| \u258f          4/200 [00:00]", "Epochs completed:   2%| \u258e          5/200 [00:00]", "Epochs completed:   3%| \u258e          6/200 [00:00]", "Epochs completed:   4%| \u258e          7/200 [00:01]", "Epochs completed:   4%| \u258d          8/200 [00:01]", "Epochs completed:   4%| \u258d          9/200 [00:01]", "Epochs completed:   5%| \u258c          10/200 [00:01]", "Epochs completed:   6%| \u258c          11/200 [00:01]", "Epochs completed:   6%| \u258c          12/200 [00:02]", "Epochs completed:   6%| \u258b          13/200 [00:02]", "Epochs completed:   7%| \u258b          14/200 [00:02]", "Epochs completed:   8%| \u258a          15/200 [00:02]", "Epochs completed:   8%| \u258a          16/200 [00:03]", "Epochs completed:   8%| \u258a          17/200 [00:03]", "Epochs completed:   9%| \u2589          18/200 [00:03]", "Epochs completed:  10%| \u2589          19/200 [00:03]", "Epochs completed:  10%| \u2588          20/200 [00:03]\tcompleted  20  /  200 epochs", "", "Epochs completed:  10%| \u2588          21/200 [00:04]", "Epochs completed:  11%| \u2588          22/200 [00:04]", "Epochs completed:  12%| \u2588\u258f         23/200 [00:04]", 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completed:  34%| \u2588\u2588\u2588\u258d       68/200 [00:15]", "Epochs completed:  34%| \u2588\u2588\u2588\u258d       69/200 [00:15]", "Epochs completed:  35%| \u2588\u2588\u2588\u258c       70/200 [00:15]", "Epochs completed:  36%| \u2588\u2588\u2588\u258c       71/200 [00:15]", "Epochs completed:  36%| \u2588\u2588\u2588\u258c       72/200 [00:16]", "Epochs completed:  36%| \u2588\u2588\u2588\u258b       73/200 [00:16]", "Epochs completed:  37%| \u2588\u2588\u2588\u258b       74/200 [00:16]", "Epochs completed:  38%| \u2588\u2588\u2588\u258a       75/200 [00:16]", "Epochs completed:  38%| \u2588\u2588\u2588\u258a       76/200 [00:16]", "Epochs completed:  38%| \u2588\u2588\u2588\u258a       77/200 [00:17]", "Epochs completed:  39%| \u2588\u2588\u2588\u2589       78/200 [00:17]", "Epochs completed:  40%| \u2588\u2588\u2588\u2589       79/200 [00:17]", "Epochs completed:  40%| \u2588\u2588\u2588\u2588       80/200 [00:17]\tcompleted  80  /  200 epochs", "", "Epochs completed:  40%| 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\u2588\u2588\u2588\u2588\u2588\u2588\u2588    140/200 [00:32]\tcompleted  140  /  200 epochs", "", "Epochs completed:  70%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588    141/200 [00:32]", "Epochs completed:  71%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588    142/200 [00:32]", "Epochs completed:  72%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258f   143/200 [00:32]", "Epochs completed:  72%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258f   144/200 [00:33]", "Epochs completed:  72%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258e   145/200 [00:33]", "Epochs completed:  73%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258e   146/200 [00:33]", "Epochs completed:  74%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258e   147/200 [00:33]", "Epochs completed:  74%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258d   148/200 [00:33]", "Epochs completed:  74%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258d   149/200 [00:34]", "Epochs completed:  75%| 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[00:36]\tcompleted  160  /  200 epochs", "", "Epochs completed:  80%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588   161/200 [00:36]", "Epochs completed:  81%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588   162/200 [00:37]", "Epochs completed:  82%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258f  163/200 [00:37]", "Epochs completed:  82%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258f  164/200 [00:37]", "Epochs completed:  82%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258e  165/200 [00:37]", "Epochs completed:  83%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258e  166/200 [00:38]", "Epochs completed:  84%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258e  167/200 [00:38]", "Epochs completed:  84%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258d  168/200 [00:38]", "Epochs completed:  84%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258d  169/200 [00:38]", "Epochs completed:  85%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258c  170/200 [00:39]", "Epochs completed:  86%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258c  171/200 [00:39]", "Epochs completed:  86%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258c  172/200 [00:39]", "Epochs completed:  86%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258b  173/200 [00:39]", "Epochs completed:  87%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258b  174/200 [00:39]", "Epochs completed:  88%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258a  175/200 [00:40]", "Epochs completed:  88%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258a  176/200 [00:40]", "Epochs completed:  88%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258a  177/200 [00:40]", "Epochs completed:  89%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2589  178/200 [00:40]", "Epochs completed:  90%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2589  179/200 [00:41]", "Epochs completed:  90%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588  180/200 [00:41]\tcompleted  180  /  200 epochs", "", "Epochs completed:  90%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588  181/200 [00:41]", "Epochs completed:  91%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588  182/200 [00:41]", "Epochs completed:  92%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258f 183/200 [00:42]", "Epochs completed:  92%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258f 184/200 [00:42]", "Epochs completed:  92%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258e 185/200 [00:42]", "Epochs completed:  93%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258e 186/200 [00:42]", "Epochs completed:  94%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258e 187/200 [00:42]", "Epochs completed:  94%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258d 188/200 [00:43]", "Epochs completed:  94%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258d 189/200 [00:43]", "Epochs completed:  95%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258c 190/200 [00:43]", "Epochs completed:  96%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258c 191/200 [00:43]", "Epochs completed:  96%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258c 192/200 [00:44]", "Epochs completed:  96%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258b 193/200 [00:44]", "Epochs completed:  97%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258b 194/200 [00:44]", "Epochs completed:  98%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258a 195/200 [00:44]", "Epochs completed:  98%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258a 196/200 [00:45]", "Epochs completed:  98%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u258a 197/200 [00:45]", "Epochs completed:  99%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2589 198/200 [00:45]", "Epochs completed: 100%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2589 199/200 [00:45]", "Epochs completed: 100%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588 200/200 [00:46]", "Epochs completed: 100%| \u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588 200/200 [00:46]", "Thu Jan 23 12:12:27 2025 Finished embedding", "writing normalized umap umap-002", "wrote /Users/enjalot/latent-scope-demo/ls-common-corpus-100k/umaps/umap-002.parquet", "POINT SIZE 30 for 100000 points", "done with umap-002"], "times": ["2025-01-23 12:10:47.094223", "2025-01-23 12:10:47.095244", "2025-01-23 12:10:50.166982", "2025-01-23 12:10:50.167255", "2025-01-23 12:10:50.819922", "2025-01-23 12:10:50.919471", "2025-01-23 12:10:50.919813", "2025-01-23 12:10:50.921386", "2025-01-23 12:10:51.006005", "2025-01-23 12:10:51.078076", "2025-01-23 12:10:51.102000", "2025-01-23 12:10:58.121518", "2025-01-23 12:11:04.665450", "2025-01-23 12:11:15.288306", "2025-01-23 12:11:26.610217", "2025-01-23 12:11:30.691608", "2025-01-23 12:11:31.892917", "2025-01-23 12:11:32.574364", "2025-01-23 12:11:33.055703", "2025-01-23 12:11:33.146920", "2025-01-23 12:11:34.503473", "2025-01-23 12:11:41.244327", "2025-01-23 12:11:41.584240", "2025-01-23 12:11:41.584507", "2025-01-23 12:11:41.734430", "2025-01-23 12:11:41.864822", "2025-01-23 12:11:42.021494", "2025-01-23 12:11:42.190301", "2025-01-23 12:11:42.376256", "2025-01-23 12:11:42.571023", "2025-01-23 12:11:42.783152", "2025-01-23 12:11:43.001059", "2025-01-23 12:11:43.221719", "2025-01-23 12:11:43.438519", "2025-01-23 12:11:43.656294", "2025-01-23 12:11:43.869060", "2025-01-23 12:11:44.084957", "2025-01-23 12:11:44.303694", "2025-01-23 12:11:44.523063", "2025-01-23 12:11:44.749158", "2025-01-23 12:11:44.974198", "2025-01-23 12:11:45.203600", "2025-01-23 12:11:45.440240", "2025-01-23 12:11:45.440535", "2025-01-23 12:11:45.675099", "2025-01-23 12:11:45.912277", "2025-01-23 12:11:46.142500", "2025-01-23 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latentscope/jobs/3304ca1d-1186-458c-a1d6-fad735e1de77.json

@@ -0,0 +1 @@
+{"id": "3304ca1d-1186-458c-a1d6-fad735e1de77", "dataset": "ls-common-corpus-100k", "job_name": "upload-dataset", "command": "ls-upload-dataset \"/Users/enjalot/latent-scope-demo/ls-common-corpus-100k\" \"ls-common-corpus-100k\" --main-parquet=\"scopes/scopes-001-input.parquet\" --private=false", "status": "running", "last_update": "2025-02-24 10:13:45.220230", "progress": ["ARGS Namespace(directory='/Users/enjalot/latent-scope-demo/ls-common-corpus-100k', dataset_name='ls-common-corpus-100k', main_parquet='scopes/scopes-001-input.parquet', private='false', token=None)", "get key /Users/enjalot/code/latent-scope", "The token has not been saved to the git credentials helper. Pass `add_to_git_credential=True` in this function directly or `--add-to-git-credential` if using via `huggingface-cli` if you want to set the git credential as well.", "Token is valid (permission: write).", "Your token has been saved to /volumes/T9/huggingface/token", "Login successful", "USERNAME enjalot", "Creating repository: ls-common-corpus-100k", "Repository created/verified: https://huggingface.co/datasets/enjalot/ls-common-corpus-100k", "DIRECTORY /Users/enjalot/latent-scope-demo/ls-common-corpus-100k"], "times": ["2025-02-24 10:13:44.779715", "2025-02-24 10:13:44.779949", "2025-02-24 10:13:44.780125", "2025-02-24 10:13:44.912017", "2025-02-24 10:13:45.131549", "2025-02-24 10:13:45.131709", "2025-02-24 10:13:45.175934", "2025-02-24 10:13:45.176158", "2025-02-24 10:13:45.219980", "2025-02-24 10:13:45.220226"]}

latentscope/jobs/b16bdc7c-7508-4db9-8f23-8b43c182a36f.json

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+{"id": "b16bdc7c-7508-4db9-8f23-8b43c182a36f", "dataset": "ls-common-corpus-100k", "job_name": "download-dataset", "command": "ls-download-dataset \"enjalot/ls-common-corpus-100k\" \"ls-common-corpus-100k\" \"/Users/enjalot/latent-scope-demo\"", "status": "completed", "last_update": "2025-01-16 22:19:50.404323", "progress": ["get key /Users/enjalot/code/latent-scope", "Warning: directory /Users/enjalot/latent-scope-demo/ls-common-corpus-100k already exists", "/Users/enjalot/code/latent-scope/testenv/lib/python3.12/site-packages/huggingface_hub/file_download.py:1212: UserWarning: `local_dir_use_symlinks` parameter is deprecated and will be ignored. The process to download files to a local folder has been updated and do not rely on symlinks anymore. You only need to pass a destination folder as`local_dir`.", "For more details, check out https://huggingface.co/docs/huggingface_hub/main/en/guides/download#download-files-to-local-folder.", "warnings.warn(", "", "Fetching 81 files:   0%|          | 0/81 [00:00<?, ?it/s]", "Fetching 81 files:   1%|          | 1/81 [00:00<00:10,  7.42it/s]", "Fetching 81 files:   4%|\u258e         | 3/81 [00:15<07:29,  5.76s/it]", "Fetching 81 files:  27%|\u2588\u2588\u258b       | 22/81 [00:36<01:30,  1.54s/it]", "Fetching 81 files:  30%|\u2588\u2588\u2589       | 24/81 [00:39<01:26,  1.51s/it]", "Fetching 81 files: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 81/81 [00:39<00:00,  2.05it/s]", "Successfully downloaded latentscope files to: /Users/enjalot/latent-scope-demo/ls-common-corpus-100k"], "times": ["2025-01-16 22:19:10.716672", "2025-01-16 22:19:10.717298", "2025-01-16 22:19:10.926547", "2025-01-16 22:19:10.926773", "2025-01-16 22:19:10.926909", "2025-01-16 22:19:10.930763", "2025-01-16 22:19:11.065764", "2025-01-16 22:19:26.534059", "2025-01-16 22:19:47.837530", "2025-01-16 22:19:50.381003", "2025-01-16 22:19:50.381438", "2025-01-16 22:19:50.381682", "2025-01-16 22:19:50.404312"]}

latentscope/jobs/e522ef51-6919-49fe-a099-9e037547ba0f.json

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latentscope/meta.json

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 {
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   "columns": [
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latentscope/scopes/scopes-001-input.parquet

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latentscope/scopes/scopes-001.json

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 {
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   "embedding_id": "embedding-001",
   "umap_id": "umap-001",
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-  "label": "\ud83e\udd17-jinaai/jina-embeddings-v3 + ollama-gemma2-2b",
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+  "label": "Common Corpus 100k",
+  "description": "100,000 sample of Common Corpus",
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+  "timestamp": "2025-02-24 10:12:22"
 }

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latentscope/umaps/umap-002.json

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