This is a quantized version based on the Pythia-70m model, specifically optimized for Wikipedia paragraph data, offering multiple quantization types to meet different resource requirements.

Natural Language ProcessingTransformersEnglish

A model pre-trained on the Pythia-1b architecture and fine-tuned on single-cell RNA sequencing data via the Cell2Sentence framework, suitable for various single-cell and multicellular analysis tasks.

Scientific ComputingTransformersEnglish

A model based on the Pythia-410m architecture, fine-tuned on single-cell RNA sequencing data using the Cell2Sentence method, suitable for various single-cell and multicellular analysis tasks.

Scientific ComputingTransformersEnglish

A cell type prediction model based on the Pythia-410m architecture, fine-tuned by converting scRNA-seq data into 'cell sentences' through the Cell2Sentence method, focusing on cell type prediction in single-cell RNA sequencing data.

Natural Language ProcessingTransformersEnglish

vortex-3b is a 2.78 billion parameter causal language model developed by OEvortex, based on the Pythia-2.8b model and fine-tuned on the Vortex-50k dataset.

Natural Language ProcessingTransformersEnglish

This is a model fine-tuned on single-cell RNA sequencing data using the Cell2Sentence method, based on the Pythia-160m language model. It is capable of conditional cell generation, unconditional cell generation, and cell type prediction.

Scientific ComputingTransformersEnglish

A 31-million parameter conversational model fine-tuned from EleutherAI/pythia-31m, supporting multi-turn dialogues and various task scenarios

Natural Language ProcessingTransformersEnglish

A causal language model based on Pythia-2.8b, fine-tuned using the Anthropic human preference dataset

Natural Language ProcessingTransformersEnglish

A causal language model based on the Pythia-6.9b foundation model, fine-tuned using Anthropic's hh-rlhf dataset for supervised training

Natural Language ProcessingTransformersEnglish

An instruction fine-tuned model developed based on the deduplicated version of Pythia 1.4B, specializing in novel creation and dialogue generation

Natural Language ProcessingTransformersEnglish

A 2.8 billion parameter instruction-finetuned large language model released by Databricks, based on the pythia-2.8b architecture, fine-tuned on 15k instruction datasets, and supports commercial use

Natural Language ProcessingTransformersEnglish

A 6.9-billion-parameter instruction-tuned large language model released by Databricks, based on Pythia-6.9b architecture, permitted for commercial use

Natural Language ProcessingTransformersEnglish

A 12-billion-parameter instruction fine-tuned large language model launched by Databricks, fine-tuned on 15K instruction data points based on pythia-12b, with commercial use permitted

Natural Language ProcessingTransformersEnglish

An English supervised fine-tuned model based on the Pythia 12B architecture, trained with human feedback data from the Open-Assistant project, focusing on dialogue generation tasks.

Natural Language ProcessingTransformersEnglish

A 7-billion-parameter open-source dialogue model fine-tuned from EleutherAI Pythia-7B, trained on over 40 million instructions using 100% carbon-negative computing resources

Natural Language ProcessingTransformersEnglish

Pythia-1B is a language model specialized for interpretability research developed by EleutherAI, belonging to the 1-billion-parameter version in the Pythia suite, trained on The Pile dataset.

Natural Language ProcessingTransformersEnglish

An instruction generation model fine-tuned on the deduplicated version of Pythia-2.8B, optimized for synthetic instruction datasets

Natural Language ProcessingTransformersEnglish

Pythia-12B is the largest model in EleutherAI's scalable language model suite, with 12 billion parameters, specifically designed to advance scientific research on large language models

Natural Language ProcessingTransformersEnglish

Pythia-12B-deduped is a large language model with 12B parameters developed by EleutherAI, designed specifically for interpretability research and trained on the deduplicated Pile dataset.

Natural Language ProcessingTransformersEnglish

Pythia-6.9B is a large-scale language model developed by EleutherAI, part of the Pythia scalable suite, specifically designed to facilitate interpretability research.

Natural Language ProcessingTransformersEnglish