Openbmb

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Average Model Cost: $0.0000

Number of Runs: 18,972

Models by this creator

cpm-ant-10b

cpm-ant-10b

openbmb

The cpm-ant-10b model is a language model that is trained to generate human-like text based on given prompts. It is built using the GPT-3 architecture, which is a transformer-based model known for its ability to generate coherent and contextually relevant text. The cpm-ant-10b model has been trained on a large corpus of text and can be used for various natural language processing tasks, such as text completion, question answering, and language translation. Its performance is evaluated using various metrics like perplexity and BLEU score to ensure its quality and effectiveness.

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14.5K

Huggingface

cpm-bee-1b

cpm-bee-1b

CPM-Bee CPM-Bee is a fully open-source, commercially-usable Chinese-English bilingual base model with a capacity of ten billion parameters. It is the second milestone achieved through the training process of CPM-live. Utilizing the Transformer auto-regressive architecture, CPM-Bee has been pre-trained on an extensive corpus of trillion-scale tokens, thereby possessing remarkable foundational capabilities. Model description Open-source and Commercial Usable´╝ÜOpenBMB adheres to the spirit of open-source, aiming to make large-scale models accessible to everyone. CPM-Bee, as a foudation model, is fully open-source and available for commercial use, contributing to the advancement of the field of large-scale models. Excellent Performance in Chinese and English´╝Ü : CPM-Bee's base model has undergone rigorous selection and balancing of pre-training data, resulting in outstanding performance in both Chinese and English. For detailed information regarding evaluation tasks and results, please refer to the assessment documentation. Vast and High-quality Corpus´╝Ü CPM-Bee, as a base model, has been trained on an extensive corpus of over trillion tokens, making it one of the models with the highest volume of training data within the open-source community. Furthermore, we have implemented stringent selection, cleaning, and post-processing procedures on the pre-training corpus to ensure its quality. Support for OpenBMB System´╝Ü The OpenBMB system provides a comprehensive ecosystem of tools and scripts for high-performance pre-training, adaptation, compression, deployment, and tool development. CPM-Bee, as a base model, is accompanied by all the necessary tool scripts, enabling developers to efficiently utilize and explore advanced functionalities. Conversational and Tool Usage Capabilities´╝Ü Building upon OpenBMB's exploration in instruction-based fine-tuning and tool learning, we have performed fine-tuning on top of the CPM-Bee base model, resulting in an instance model with powerful conversational and tool usage capabilities. The API and beta testing for this model will be made available in the near future. Intended uses & limitations You can use the raw model for many NLP tasks like text generation or fine-tune it to a downstream task. How to use If you wanna use multi GPUs to inference, you can use accelerate as follow: We suggest to use bmtrain to finetune CPM-Bee. Also, you can use accelerate and deepspeed to finetune CPM-Bee. Here we will give a brief example of a training loop: You should design your own parallel and mix_precision training strategy on the basis of it.

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885

Huggingface

cpm-bee-5b

cpm-bee-5b

CPM-Bee CPM-Bee is a fully open-source, commercially-usable Chinese-English bilingual base model with a capacity of ten billion parameters. It is the second milestone achieved through the training process of CPM-live. Utilizing the Transformer auto-regressive architecture, CPM-Bee has been pre-trained on an extensive corpus of trillion-scale tokens, thereby possessing remarkable foundational capabilities. Model description Open-source and Commercial Usable´╝ÜOpenBMB adheres to the spirit of open-source, aiming to make large-scale models accessible to everyone. CPM-Bee, as a foudation model, is fully open-source and available for commercial use, contributing to the advancement of the field of large-scale models. Excellent Performance in Chinese and English´╝Ü : CPM-Bee's base model has undergone rigorous selection and balancing of pre-training data, resulting in outstanding performance in both Chinese and English. For detailed information regarding evaluation tasks and results, please refer to the assessment documentation. Vast and High-quality Corpus´╝Ü CPM-Bee, as a base model, has been trained on an extensive corpus of over trillion tokens, making it one of the models with the highest volume of training data within the open-source community. Furthermore, we have implemented stringent selection, cleaning, and post-processing procedures on the pre-training corpus to ensure its quality. Support for OpenBMB System´╝Ü The OpenBMB system provides a comprehensive ecosystem of tools and scripts for high-performance pre-training, adaptation, compression, deployment, and tool development. CPM-Bee, as a base model, is accompanied by all the necessary tool scripts, enabling developers to efficiently utilize and explore advanced functionalities. Conversational and Tool Usage Capabilities´╝Ü Building upon OpenBMB's exploration in instruction-based fine-tuning and tool learning, we have performed fine-tuning on top of the CPM-Bee base model, resulting in an instance model with powerful conversational and tool usage capabilities. The API and beta testing for this model will be made available in the near future. Intended uses & limitations You can use the raw model for many NLP tasks like text generation or fine-tune it to a downstream task. How to use If you wanna use multi GPUs to inference, you can use accelerate as follow: We suggest to use bmtrain to finetune CPM-Bee. Also, you can use accelerate and deepspeed to finetune CPM-Bee. Here we will give a brief example of a training loop: You should design your own parallel and mix_precision training strategy on the basis of it.

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553

Huggingface

cpm-bee-2b

cpm-bee-2b

CPM-Bee CPM-Bee is a fully open-source, commercially-usable Chinese-English bilingual base model with a capacity of ten billion parameters. It is the second milestone achieved through the training process of CPM-live. Utilizing the Transformer auto-regressive architecture, CPM-Bee has been pre-trained on an extensive corpus of trillion-scale tokens, thereby possessing remarkable foundational capabilities. Model description Open-source and Commercial Usable´╝ÜOpenBMB adheres to the spirit of open-source, aiming to make large-scale models accessible to everyone. CPM-Bee, as a foudation model, is fully open-source and available for commercial use, contributing to the advancement of the field of large-scale models. Excellent Performance in Chinese and English´╝Ü : CPM-Bee's base model has undergone rigorous selection and balancing of pre-training data, resulting in outstanding performance in both Chinese and English. For detailed information regarding evaluation tasks and results, please refer to the assessment documentation. Vast and High-quality Corpus´╝Ü CPM-Bee, as a base model, has been trained on an extensive corpus of over trillion tokens, making it one of the models with the highest volume of training data within the open-source community. Furthermore, we have implemented stringent selection, cleaning, and post-processing procedures on the pre-training corpus to ensure its quality. Support for OpenBMB System´╝Ü The OpenBMB system provides a comprehensive ecosystem of tools and scripts for high-performance pre-training, adaptation, compression, deployment, and tool development. CPM-Bee, as a base model, is accompanied by all the necessary tool scripts, enabling developers to efficiently utilize and explore advanced functionalities. Conversational and Tool Usage Capabilities´╝Ü Building upon OpenBMB's exploration in instruction-based fine-tuning and tool learning, we have performed fine-tuning on top of the CPM-Bee base model, resulting in an instance model with powerful conversational and tool usage capabilities. The API and beta testing for this model will be made available in the near future. Intended uses & limitations You can use the raw model for many NLP tasks like text generation or fine-tune it to a downstream task. How to use If you wanna use multi GPUs to inference, you can use accelerate as follow: We suggest to use bmtrain to finetune CPM-Bee. Also, you can use accelerate and deepspeed to finetune CPM-Bee. Here we will give a brief example of a training loop: You should design your own parallel and mix_precision training strategy on the basis of it.

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283

Huggingface

UltraLM-13b

UltraLM-13b

UltraLM-13b This is UltraLM-13b delta weights, a chat language model trained upon UltraChat Model Details Model Description The model is fine-tuned based on LLaMA-13b with a multi-turn chat-format template as below License: UltraLM is based on LLaMA and should be used under LLaMA's model license. Finetuned from model: LLaMA-13b Finetuned on data: UltraChat Model Sources Repository: UltraChat Paper: arxiv Demo: [More Information Needed] Uses To use this model, you need to recover the full model from the delta weights and perform inference following the template below:

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171

Huggingface

VisCPM-Paint

VisCPM-Paint

VisCPM is a family of open-source large multimodal models, which support multimodal conversational capabilities (VisCPM-Chat model) and text-to-image generation capabilities (VisCPM-Paint model) in both Chinese and English, achieving state-of-the-art peformance among Chinese open-source multimodal models. VisCPM is trained based on the large language model CPM-Bee with 10B parameters, fusing visual encoder (Q-Former) and visual decoder (Diffusion-UNet) to support visual inputs and outputs. Thanks to the good bilingual capability of CPM-Bee, VisCPM can be pre-trained with English multimodal data only and well generalize to achieve promising Chinese multimodal capabilities. ­čĹÉ Open-source Usage: VisCPM is free to be used for personal and research purposes. By open-sourcing the VisCPM model family, we hope to promote the development of the open-source community of large multimodal models and related research. ­čîč Image and text generation coverage: VisCPM models provide relatively comprehensive support for image and text multimodal capabilities, covering both multimodal conversation (image-to-text generation) capabilities and text-to-image generation capabilities. ­čĺź Excellent bilingual performance: Thanks to the excellent bilingual capability of the base language model CPM-Bee, VisCPM achieves outstanding results in both bilingual multimodal conversation and text-to-image generation. VisCPM-Paint VisCPM-Paint supports bilingual text-to-image generation. The model uses CPM-Bee as the text encoder, UNet as the image decoder, and fuses vision and language models using the objective of diffusion model. During the training process, the parameters of the language model remain fixed. The visual decoder is initialized with the parameters of Stable Diffusion 2.1, and it is fused with the language model by gradually unfreezing key bridging parameters. The model is trained on the LAION 2B English text-image pair dataset. Similar to VisCPM-Chat, we found that due to the bilingual capability of CPM-Bee, VisCPM-Paint can achieve good Chinese text-to-image generation by training only on English text-image pairs, surpassing the performance of Chinese open-source models. By incorporating an additional 20M cleaned native Chinese text-image pairs and 120M translated text-image pairs in Chinese, the model's Chinese text-to-image generation ability can be further improved. We sample 30,000 images from the standard image generation test set MSCOCO and calculated commonly used evaluation metrics FID (Fr├ęchet Inception Distance) to assess the quality of generated images. Similarly, we provide two versions of the model, namely VisCPM-Paint-balance and VisCPM-Paint-zhplus. The former has a balanced ability in both English and Chinese, while the latter emphasizes Chinese proficiency. VisCPM-Paint-balance is trained only using English text-image pairs, while VisCPM-Paint-zhplus incorporates an additional 20M native Chinese text-image pairs and 120M translated text-image pairs in Chinese based on VisCPM-Paint-balance. ­čôŁ License VisCPM is governed by the GML License, and permits individual and research usages. If you intend to utilize the model for commercial purposes, please reach out to cpm@modelbest.cn to negotiate commercial licensing. The CPM-Bee base, governed by the General Model License (GML), permits commercial usage. If you intend to utilize the model for commercial purposes, please reach out to cpm@modelbest.cn to obtain the certificate of authorization.

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6

Huggingface

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