t5-v1_1-xxl-encoder-gguf
Maintainer: city96
118
🛠️
| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
Create account to get full access
Model overview
The t5-v1_1-xxl-encoder-gguf is a GGUF conversion of Google's T5 v1.1 XXL encoder model, created by the maintainer city96. This model can be used with the [object Object] tool or the ComfyUI-GGUF custom node, in conjunction with image generation models.
Model inputs and outputs
The t5-v1_1-xxl-encoder-gguf model takes in text-based inputs and generates text-based outputs. It is a non-imatrix quantized version, so it is recommended to use a Q5_K_M or larger quantization for the best results, although smaller models may still provide decent results in resource-constrained scenarios.
Inputs
- Text-based inputs that the model can process and generate outputs from
Outputs
- Text-based outputs generated by the model based on the provided inputs
Capabilities
The t5-v1_1-xxl-encoder-gguf model can be used for a variety of text-based tasks, such as text generation, language modeling, and potentially image-to-text tasks when combined with the appropriate tools and custom nodes.
What can I use it for?
The t5-v1_1-xxl-encoder-gguf model can be used in a wide range of applications, such as content creation, language translation, and even image-to-text tasks when paired with the right tools and custom nodes. It can be particularly useful for resource-constrained scenarios where a smaller, quantized version of the model may still provide decent results.
Things to try
One interesting thing to try with the t5-v1_1-xxl-encoder-gguf model is to experiment with different quantization levels, such as Q5_K_M or larger, to see how it affects the model's performance and outputs. You can also try using the model with the [object Object] tool or the ComfyUI-GGUF custom node to integrate it into various projects and workflows.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
Related Models
🛠️
t5-v1_1-xxl-encoder-gguf
118
The t5-v1_1-xxl-encoder-gguf is a GGUF conversion of Google's T5 v1.1 XXL encoder model, created by the maintainer city96. This model can be used with the ./llama-embedding tool or the ComfyUI-GGUF custom node, in conjunction with image generation models. Model inputs and outputs The t5-v1_1-xxl-encoder-gguf model takes in text-based inputs and generates text-based outputs. It is a non-imatrix quantized version, so it is recommended to use a Q5_K_M or larger quantization for the best results, although smaller models may still provide decent results in resource-constrained scenarios. Inputs Text-based inputs that the model can process and generate outputs from Outputs Text-based outputs generated by the model based on the provided inputs Capabilities The t5-v1_1-xxl-encoder-gguf model can be used for a variety of text-based tasks, such as text generation, language modeling, and potentially image-to-text tasks when combined with the appropriate tools and custom nodes. What can I use it for? The t5-v1_1-xxl-encoder-gguf model can be used in a wide range of applications, such as content creation, language translation, and even image-to-text tasks when paired with the right tools and custom nodes. It can be particularly useful for resource-constrained scenarios where a smaller, quantized version of the model may still provide decent results. Things to try One interesting thing to try with the t5-v1_1-xxl-encoder-gguf model is to experiment with different quantization levels, such as Q5_K_M or larger, to see how it affects the model's performance and outputs. You can also try using the model with the ./llama-embedding tool or the ComfyUI-GGUF custom node to integrate it into various projects and workflows.
Updated Invalid Date
⚙️
FLUX.1-dev-gguf
424
The FLUX.1-dev-gguf is a direct conversion of the FLUX.1-dev model created by city96. This quantized model can be used with the ComfyUI-GGUF custom node for image-to-image tasks. Model inputs and outputs The FLUX.1-dev-gguf model takes in images and outputs transformed images. The specific inputs and outputs are: Inputs Images Outputs Transformed images Capabilities The FLUX.1-dev-gguf model can be used for a variety of image-to-image tasks, such as style transfer, super-resolution, and image manipulation. It is a powerful tool for creative applications and content generation. What can I use it for? The FLUX.1-dev-gguf model can be used for a range of creative and generative applications. For example, you could use it to transform existing images into new artistic styles, generate unique image variations, or enhance the quality of low-resolution images. The model's capabilities make it a valuable tool for designers, artists, and content creators looking to streamline their workflow and explore new creative possibilities. Things to try With the FLUX.1-dev-gguf model, you can experiment with different input images and see how the model transforms them. Try feeding in a variety of subject matter, styles, and resolutions to see the range of outputs the model can produce. Additionally, you can combine the model with other image processing techniques to create even more compelling and unique results.
Updated Invalid Date
🔎
FLUX.1-schnell-gguf
118
FLUX.1-schnell-gguf is a direct GGUF conversion of the FLUX.1-schnell model developed by black-forest-labs. It is a powerful image generation model capable of producing high-quality images from text descriptions. Like its predecessor, FLUX.1-schnell-gguf utilizes a rectified flow transformer architecture and was trained using latent adversarial diffusion distillation, allowing it to generate images in just 1-4 steps. Model inputs and outputs FLUX.1-schnell-gguf is an image-to-image model, taking in text descriptions and outputting corresponding images. The model can be used with the ComfyUI-GGUF custom node. Inputs Text descriptions or prompts Outputs High-quality generated images Capabilities FLUX.1-schnell-gguf demonstrates impressive output quality and prompt following capabilities, matching the performance of closed-source alternatives. The model can generate detailed and visually striking images from a wide range of text prompts. What can I use it for? FLUX.1-schnell-gguf can be a powerful tool for creative applications, such as generating custom artwork, illustrations, or concept designs. The model's speed and versatility make it suitable for use in various industries, including marketing, game development, and visual effects. Additionally, the model's Apache 2.0 license allows for personal, scientific, and commercial use. Things to try One interesting aspect of FLUX.1-schnell-gguf is its ability to generate images in just 1-4 steps, thanks to its latent adversarial diffusion distillation training. This makes the model particularly efficient and well-suited for real-time or interactive applications. Developers and creators are encouraged to explore the model's capabilities and integrate it into their projects using the provided resources.
Updated Invalid Date
👀
Llama-3.1-8B-Lexi-Uncensored-V2-GGUF
52
Llama-3.1-8B-Lexi-Uncensored-V2-GGUF is an AI model based on the Llama-3.1-8B-Instruct model and developed by Orenguteng. This model is designed to provide more compliant and smarter responses compared to the original Llama-3.1-8B-Instruct model. It is governed by the META LLAMA 3.1 COMMUNITY LICENSE AGREEMENT. Model inputs and outputs The Llama-3.1-8B-Lexi-Uncensored-V2-GGUF model is a text-to-text AI model, meaning it takes text as input and generates text as output. Inputs Text prompts that the model uses to generate a response Outputs Text responses generated by the model based on the input prompts Capabilities The Llama-3.1-8B-Lexi-Uncensored-V2-GGUF model is designed to be more compliant and smarter than the original Llama-3.1-8B-Instruct model. It can provide responses that are more logical and intellectual in nature. What can I use it for? The Llama-3.1-8B-Lexi-Uncensored-V2-GGUF model can be used for a variety of text-based tasks, such as content generation, dialogue systems, and language modeling. However, it is important to note that the model is uncensored, and users are responsible for any content they create using it. It is advised to implement an alignment layer before exposing the model as a service. Things to try When using the Llama-3.1-8B-Lexi-Uncensored-V2-GGUF model, it is recommended to use the provided system prompt or to expand upon it as needed. This can help the model provide more compliant and smarter responses. Additionally, users may want to experiment with different input prompts and settings to see how the model performs on various tasks.
Updated Invalid Date