exp4_averaged
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言語から画像、オープンウェイトからAPIまで。能力と実際の費用を比較。
次のアイデアに合うAIを見つけましょう。
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This model is a text classification model based on Deberta-v3 that predicts whether a text contains text that could be considered offensive. It is split up in the following labels: It's important to remember that this model was only trained on English texts, and may not perform well on non-English inputs. This is a model that deals with sensitive and potentially harmful language. Users should consider the ethical implications and potential risks of using or deploying this model in their applications or contexts. Some of the ethical issues that may arise are:
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> **Ungated mirror of black-forest-labs/flux-3-image-klein-comfy.** > All credit to Black Forest Labs — this is not an official Black Forest Labs > release and is not endorsed by them. The weights are redistributed under the > FLUX Kommunity License, included here as `LICENSE.md` together > with `NOTICE.md`; any rights to use them are granted directly by > Black Forest Labs under that licence. > > **What this mirror carries** — the int8 / w4a8 builds the ComfyUI templates and > the SAUS apps use: > > | path | size | what it is | > | --- | --- | --- | > | `diffusion_models/flux3_image_klein_base_int8_convrot.safetensors` | 5.81 GB | Klein Base, undistilled — 50 steps, guidance 3.5 | > | `diffusion_models/flux3_image_klein_sd_int8_convrot.safetensors` | 5.83 GB | Klein distilled — 16 steps, no guidance | > | `text_encoders/qwen3vl_4b_int8_convrot.safetensors` | 4.86 GB | Qwen3-VL-4B-Instruct text encoder | > | `text_encoders/qwen3.5_9b_flux3_prompt_upsampler_w4a8.safetensors` | 6.72 GB | prompt upsampler | > | `vae/flux2-vae.safetensors` | 336 MB | image autoencoder | > > **Installing into ComfyUI:** copy (or symlink) `diffusion_models/` and > `text_encoders/` into `ComfyUI/models/`, and `vae/flux2-vae.safetensors` into > `ComfyUI/models/vae/`. The sub-folder layout above deliberately matches the > upstream repository, so a plain directory copy is enough. FLUX 3 Image Klein is a 5.6B open weights model for text-to-image generation and image editing. It takes a prompt and up to 10 reference images and returns one image. Text-to-image, single-reference edits and multi-reference compositions run through the same model, with Qwen3-VL-4B-Instruct as the text encoder. The 5.6B parameter label refers to the image transformer; the text encoder is separate.
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This is the GGUF version of the model meant for use in KoboldCpp, check the Float16 version for the original. Tiefighter is a merged model achieved trough merging two different lora's on top of a well established existing merge. To achieve this the following recipe was used: This means this model contains the following ingredients from their upstream models for as far as we can track them: - Undi95/Xwin-MLewd-13B-V0.2 - - Undi95/ReMM-S-Light - Undi95/CreativeEngine - Brouz/Slerpeno - - elinas/chronos-13b-v2 - jondurbin/airoboros-l2-13b-2.1 - NousResearch/Nous-Hermes-Llama2-13b+nRuaif/Kimiko-v2 - CalderaAI/13B-Legerdemain-L2+lemonilia/limarp-llama2-v2 - - KoboldAI/LLAMA2-13B-Holodeck-1 - NousResearch/Nous-Hermes-13b - OpenAssistant/llama2-13b-orca-8k-3319 - ehartford/WizardLM-1.0-Uncensored-Llama2-13b - Henk717/spring-dragon - The-Face-Of-Goonery/Huginn-v3-13b (Contains undisclosed model versions, those we assumed where possible) - - SuperCOT (Undisclosed version) - elinas/chronos-13b-v2 (Version assumed) - NousResearch/Nous-Hermes-Llama2-13b - stabilityai/StableBeluga-13B (Version assumed) - zattio770/120-Days-of-LORA-v2-13B - PygmalionAI/pygmalion-2-13b - Undi95/Storytelling-v1-13B-lora - TokenBender/sakhi_13B_roleplayer_NSFW_chat_adapter - nRuaif/Kimiko-v2-13B - The-Face-Of-Goonery/Huginn-13b-FP16 - - "a lot of different models, like hermes, beluga, airoboros, chronos.. limarp" - lemonilia/LimaRP-Llama2-13B-v3-EXPERIMENT - Xwin-LM/Xwin-LM-13B-V0.2 - PocketDoc/Dans-RetroRodeo-13b - Blackroot/Llama-2-13B-Storywriter-LORA While we could possibly not credit every single lora or model involved in this merged model, we'd like to thank all involved creators upstream for making this awesome model possible! Thanks to you the AI ecosystem is thriving, and without your dedicated tuning efforts models such as this one would not be possible.
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提供元・分類・入出力の条件を変更してください。新しいモデルを随時追加しています。
月間トークン数を調整してAPI費用を比較。
収集済みの比較可能な100万トークン当たり米ドル料金です。キャッシュ割引、段階料金、追加推論出力、税金は含みません。最新料金は出典で確認してください。
入力・出力・キャッシュ料金を分け、同じ用途と使用量で総費用を比較します。画像・音声・動画は枚数、時間、解像度で課金される場合があります。
必ずしもそうではありません。バージョンごとのライセンス、商用制限、ポリシーを確認してください。自前運用には計算資源と保守費用も必要です。
順位はテスト、バージョン、評価方法によります。実際の業務データで精度、遅延、安定性、費用を比較してください。