# English language model

Marin 8B is an open-source large language model with a scale of 8B parameters, developed based on the Llama architecture and supports English text generation tasks.

Falcon-E-1B-Instruct is an efficient language model based on a 1.58-bit architecture, optimized for edge devices with low memory footprint and high performance.

Falcon-E is a 1.58-bit quantized language model developed by TII, featuring a pure Transformer architecture designed for efficient inference

OLMo 2 32B is the largest 32B-parameter model in the open language model series released by the Allen Institute for AI (AI2). It is open-sourced under the Apache 2.0 license and supports English language processing.

A quantized version based on the m-a-p/YuE-s1-7B-anneal-en-cot model using Exllamav2, suitable for text generation tasks, particularly excelling in music-related fields.

A Transformer-based language model released by OpenAI, pre-trained on large-scale corpora with powerful text generation capabilities

BTLM-3B-8k-base is a 3-billion-parameter language model with an 8k context length, trained on the 627-billion-token SlimPajama dataset, delivering performance comparable to open-source 7-billion-parameter models.

GPT-2 is an autoregressive language model based on the Transformer architecture. It is pre-trained on a large-scale English corpus through self-supervised learning and excels at text generation tasks.

A Transformer model pre-trained on English corpus using ELECTRA-like objective functions, learning intrinsic representations of English language through self-supervised methods.

A RoBERTa model pretrained on a small-scale dataset of 1M tokens, using the MED-SMALL architecture, suitable for text understanding tasks.

A lightweight text classification model based on DistilBERT, fine-tuned on the GLUE CoLA task for judging grammatical correctness of sentences

Transformer-XL is a causal Transformer architecture that uses relative position encoding. It can capture longer context by reusing previously computed hidden states, making it suitable for text generation tasks.

GPT-Neo 2.7B is a 2.7 billion parameter Transformer language model replicated by EleutherAI based on the GPT-3 architecture, trained on the Pile dataset