Created by: qBittorrent v4.6.4
| Path (35 files) | Size | BTMR hash ? BitTorrent Merkle Root is a hash of a file embedded in torrents with BitTorrent v2 support, tracker users can extract, calculate them, also download deduplicated torrents using desktop tools such as Torrent Merkle Root Reader. |
|---|---|---|
| README.md | 3.57 KB | 1556f7a097b43748bedd571de523404abde7e77584178311ff1494184f0e06fd |
| added_tokens.json | 1.05 KB | eca8e90d1be6af3afeb1a37f070f9492645c551a9fb2e1ce2a4a8b21f04ffc8b |
| assets/demo-1.jpg | 278.01 KB | e7096d260b26580808573661cb39071f110188160ec4a77e2204ddd564418918 |
| assets/demo-2.jpg | 135.88 KB | 4609f5c76bdfb7881436c88be8085ef1fbf5dba1e52f5e576cf30c2e7f8a7e9c |
| assets/demo-3.jpg | 69.1 KB | f1d4ab59dd3bd34c8380354e0b28b052e90289f21b5e31ea0f024b29ceb5f732 |
| assets/demo-4.jpg | 29.48 KB | f312571e8799d7dd506cfa960bfebe8adf06435f183ecf9b31be792ccd2a9824 |
| assets/demo-5.jpg | 9.29 KB | aae65c0528d0fd3d6fc9df4114986118285075e1e4560ca287edea7ad019f53e |
| config.json | 323 B | 426ecbf99e0a057f55f162ba97479bdd6b7ed1759c4f966db38cd5fe3255500b |
| configuration_moondream.py | 2.29 KB | a9b4d5c6409b18492c4c4f0d28869edad6c391a3e2ff58376cc79030d1c72252 |
| generation_config.json | 69 B | d8b3d56ccdc67e074c7923b07d778721d2d6212bacb344e97f9464fde1b7f29d |
| llava.projector | 856 B | 5832d6ff84b419a2187d819ede3c1c1d234c9967f59015f930845d3dd0ff8e1b |
| merges.txt | 445.62 KB | bf2a96d700005e747dfb1b5963105bd973f534e4b0b33df698487bc0c2efd1c1 |
| mmproj-model-f16.gguf | 555.48 MB | 3b46e6c61abf40fab9fab333195fc18a28f17b4410e2fe2fb0e423f8ae2d7d03 |
| model-00001-of-00002.safetensors | 4.65 GB | 80ced9ad5b1757a54957560d681f709971693848d50f602765b757a6f8c2c61f |
| model-00002-of-00002.safetensors | 2.39 GB | addfc9afe24a6350f75fcc4e98cbb645480c8e3db95aab2e4a5578534952995c |
| model.safetensors | 3.46 GB | e1daa9c9431cdb6740cc6baf364da095f824f7bfd28d3009544ae7b41915b2d0 |
| model.safetensors.index.json | 57.61 KB | 6d0172a5b0b408e08f02b9ddb4f980bc8f7953b14ebd0be5c5505cb1a51a9858 |
| modeling_phi.py | 24.75 KB | 1db697a6b2b111a52b2e29f3cb89f8c2a44e493ecb85dc8a6226b32e6e4f81b1 |
| moondream.py | 3.16 KB | eee1f06d3c7ea9ab1839644d6db5c1c7843ee0ebb33fa493b01bac6333b855da |
| pytorch_model.bin | 7.04 GB | 40258a53fb5e9d3f3bb1fc504c190b994f80c5a9c63b5e0ec7cef23d9fc043b2 |
| special_tokens_map.json | 441 B | 10b8c8852c1e1f70b54d9aff61728408c28971c0e97a6c5a7b2debbd1d3e9c0c |
| text_model.pt | 2.64 GB | a86b8e65dfedb3e26887f5bda45ffa5b705744e8317e7d02d5ccdc0322a4c985 |
| text_model.py | 535 B | b918a6548a4f4bec91a0d583c279178304c3ca6271fbc339929f9c329d4cf215 |
| text_model_cfg.json | 795 B | 66d61f1058a57b445fad070db2ab50872474535ea14507374ab0163f905dcb18 |
| tokenizer/added_tokens.json | 1.05 KB | eca8e90d1be6af3afeb1a37f070f9492645c551a9fb2e1ce2a4a8b21f04ffc8b |
| tokenizer/merges.txt | 445.62 KB | bf2a96d700005e747dfb1b5963105bd973f534e4b0b33df698487bc0c2efd1c1 |
| tokenizer/special_tokens_map.json | 99 B | 6f50ab5a5a509a1c309d6171f339b196a900dc9c99ad0408ff23bb615fdae7ad |
| tokenizer/tokenizer.json | 2.02 MB | ca8a0891d499e9aec05b9c30135b8327dff98f5cb70d85377c7f2bd39f26fadd |
| tokenizer/tokenizer_config.json | 7.17 KB | 1906c7514a738bd743a05d7d95c8e9aeddb4d8c9ffdda4fb6ee05653fb6b97c4 |
| tokenizer/vocab.json | 779.45 KB | 0499775a02ccdd3fc198fa4012c83da9d8b30da564e2515f6d1efe137a80c374 |
| tokenizer.json | 2.02 MB | ca8a0891d499e9aec05b9c30135b8327dff98f5cb70d85377c7f2bd39f26fadd |
| tokenizer_config.json | 7.17 KB | 1906c7514a738bd743a05d7d95c8e9aeddb4d8c9ffdda4fb6ee05653fb6b97c4 |
| vision.pt | 1.76 GB | a569ec079ea34bfc854d52e1882fa5d0fb8a439f6c462f81a99be4bbcd2964fd |
| vision_encoder.py | 3.46 KB | 9d4ca49fd0a8c4603c0273150881dfbaef676d0135549b1015044ae7bd2226b4 |
| vocab.json | 779.45 KB | 0499775a02ccdd3fc198fa4012c83da9d8b30da564e2515f6d1efe137a80c374 |
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