Bigscience

Rank:

Average Model Cost: $0.0000

Number of Runs: 2,102,909

Models by this creator

bloom-560m

bloom-560m

bigscience

The bloom-560m is a text generation model that has been trained on a large amount of data. Its purpose is to generate coherent and contextually relevant text based on a given prompt. This model can be used in various applications such as natural language processing, chatbots, and content generation.

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$-/run

1.7M

Huggingface

bloom-intermediate

bloom-intermediate

The model is a technical model that is designed to perform a specific task or function. The creator did not provide a description for this model, so it is not clear what exact task or function it is meant to perform. However, based on the name "bloom-intermediate," it is possible that the model is related to the field of computer graphics or animation, as the term "bloom" often refers to a visual effect used to create a glowing or radiant appearance. Additionally, the term "intermediate" suggests that the model may be suited for intermediate-level tasks or applications in this field. Without more information, it is difficult to determine the specific capabilities or features of the model.

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$-/run

118.3K

Huggingface

bloomz-7b1-mt

bloomz-7b1-mt

The bloomz-7b1-mt model is part of the BLOOMZ model family developed for the BigScience project. It is a multilingual model that can perform various natural language processing tasks. It can be used for tasks such as translation, summarization, question answering, and text generation. The model has been trained on a large amount of multilingual data using a multitask finetuning approach. It has limitations in terms of prompt engineering and may require clear and context-rich prompts for optimal performance. The model architecture, training details, and evaluation results are provided in the documentation.

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$-/run

68.7K

Huggingface

bloom-7b1

bloom-7b1

The bloom-7b1 model is a text generation model built for tasks such as natural language understanding, sentiment analysis, and language generation. It is designed to generate human-like text responses based on natural language prompts. The model has been trained on a large and diverse dataset of text, which enables it to generate coherent and contextually relevant responses. It can be used in a variety of applications that require text generation, such as chatbots, virtual assistants, or content generation.

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$-/run

52.7K

Huggingface

bloomz-7b1

bloomz-7b1

The bloomz-7b1 model is a language model that has been trained on a diverse range of languages. It is designed to perform tasks expressed in natural language. For example, it can be used for translation, text generation, and question answering. The model has been trained using a multitask finetuning approach, and it has undergone extensive evaluation to ensure its performance. However, it has some limitations, such as sensitivity to prompt engineering and the need for clear context. The model has been trained using powerful hardware and software, and it has achieved good performance in zero-shot evaluation. To use the model, prompts can be provided in various languages with clear instructions to obtain the desired output.

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$-/run

35.8K

Huggingface

bloomz-560m

bloomz-560m

The bloomz-560m model is a language generation model that is a member of the BLOOMZ and mT0 model family. It can be used to perform various natural language processing tasks, such as translation, summarization, and question answering. The model has been trained using multitask finetuning and has been evaluated on a range of tasks. It has limitations in terms of prompt engineering, where the performance may vary depending on the prompt used. The model has been trained using a large amount of data and has been fine-tuned using a combination of pipeline parallelism, tensor parallelism, and data parallelism. The model can be used on CPU and GPU hardware, and the training process has been orchestrated using Megatron-DeepSpeed. The model is available for citation.

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$-/run

28.9K

Huggingface

bloom-1b1

bloom-1b1

The bloom-1b1 model is a text generation model that has been trained on a large corpus of text data. It is designed to generate coherent and relevant text based on a given input prompt. The model uses the GPT-3 architecture and has been fine-tuned on a wide range of tasks and domains. It can be used for various applications such as writing articles, generating code, answering questions, and more. The model is particularly effective at producing creative and engaging content, making it a valuable tool for content generation and language understanding tasks.

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$-/run

25.8K

Huggingface

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