打开train 选项卡,在 Create embedding 选项卡新建一个 embedding 模型。 Number of vectors per token 是 embedding 的宽度,与数据集有关,如果少于 百张,可以设置 3。 宽度越大时效果越强,但是需要数万轮训练。 据usim-U的视频,设置 24 至少需要三百张高质量作品。 Name 输入框输入你预想的出现此人设的 提示...
当Number of vectors per token 为 6 时: 当Number of vectors per token 为 30 时: 可以明显看出来Number of vectors per token越大训练角色特征会保留得更多 Overwrite Old Embedding:在创建时会重置原pt文件(此时pt文件重新为空,且从第一步开始训练)[记得覆盖后重启,不然会发现没有重置] 2.Preprocess image...
每个词元 token 的向量数(Number of vectors per token)参数滑块:通过该参数调整滑块来调整 Embedding 的大小的。值越大,嵌入进 Embedding 的新概念信息越多。在 Stable Diffusion 中默认的提示词输入最大量为不超过75个,如果在 Embedding 中嵌入了 10 个 token ,那就意味着节省出了10个 token的输入空间,即一个...
So when you leave it 1 by default, it takes only first token from all string. Enjoy! 1 0 replies dragonplus-wby Jul 27, 2023 Those who adjust the Prompt template has no effect can check whether the Number of vectors per token was not adjusted when Create embedding, this will also c...
After importing the ONNX embedding model into the Database, you can generate embedding vectors using theVECTOR_EMBEDDINGSQL scoring function. TheVECTOR_EMBEDDINGSQL scoring function returnsVECTOR(dimension, type). The embedding models define the number of dimensions of the output vector of theVECTOR_...
Click Create embedding (leaving Number of vectors per token = 1) Generate an image with prompt test and observe "TI hashes" in metadata Do you get any error here? Copy link Author maxxrox commented Mar 25, 2024 Windows 10; desktop PC, Intel i7-9700K processor, 32GB RAM, nVidia 2080...
Convert an array of tokenized documents to sequences of word vectors using a pretrained word embedding. Load a pretrained word embedding using thefastTextWordEmbeddingfunction. This function requires Text Analytics Toolbox™ Modelfor fastText English 16 Billion Token Word Embeddingsupport package. If ...
16K token context length, well-suited for applications on long documents. Latency is 90 ms for a single query with at most 100 tokens. 12.6M tokens per hour at $0.22 per 1M tokens on an ml.g6.xlarge. See other embedding models:voyage-3,voyage-3-lite,voyage-code-2,voyage-law-2,voya...
Number of vectors per token: the size of embedding. The larger this value, the more information about subject you can fit into the embedding, but also the more words it will take away from your prompt allowance. With stable diffusion, you have a limit of 75 tokens in the prompt. If you...
If prompting for something like "brad pitt" is enough to get Brad Pitt's likeness in stable diffusion 1.5, and it only uses 2 tokens (words), then it should be possible to capture another person's likeness with only 2 vectors per token. ...