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LLM List Based on «AutoModelForCausalLM» LLM Architecture Was this list helpful?

Searching for new models built with the AutoModelForCausalLM architecture? Our directory features a diverse range of small and large language models (SLMs and LLMs) specifically designed using it.
Discover the latest in language model technology, with models ranging in size from 3b to 70b, all utilizing HuggingFace transformers with the ready-to-use AutoModelForCausalLM class. Compare them based on processing power, advanced features, and their unique capabilities tailored for various computational tasks.
Which of these models excel in specific areas and achieve the highest benchmarks? Our comprehensive directory answers these questions, presenting the newest models built with the AutoModelForCausalLM architecture in a clear and concise manner.
For the latest innovations in language modeling, particularly those leveraging the AutoModelForCausalLM architecture, our list is an essential resource. Explore our table below, which showcases both SLMs and LLMs, and find the perfect model that fits your specific needs and tasks. Unlock the potential of 'AutoModelForCausalLM' LLM architecture!
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LLM List Based on «AutoModelForCausalLM» LLM Architecture
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Here comes the list of the Small and Large Language Models
Model Name Maintainer Size Score VRAM (GB) Quantized License Context Len Likes Downloads Modified Languages Architectures
— Large Language Model
— Adapter
— Code-Generating Model
— Listed on LMSys Arena Bot ELO Rating
— Original Model
— Merged Model
— Instruction-Based Model
— Quantized Model
— Finetuned Model
— Mixture-Of-Experts
Table Headers Explained  
  • Name — The title and maintainer account associated with the model.
  • Params — The number of parameters used in the model.
  • Score — The model's score depending on the selected rating (default is the Open LLM Leaderboard on HuggingFace).
  • Likes — The number of "likes" given to the model by users.
  • VRAM — The number of GB required to load the model into the memory. It is not the actual required amount of RAM for inference, but could be used as a reference.
  • Downloads — The total number of downloads for the model.
  • Quantized — Specifies whether the model is quantized.
  • CodeGen — Specifies whether the model can recognize or infer source code.
  • License — The type of license associated with the model.
  • Languages — The list of languages supported by the model (where specified).
  • Maintainer — The author or maintainer of the model.
  • Architectures — The transformer architecture used in the model.
  • Context Len — The content length supported by the model.
  • Tags — The list of tags specified by the model's maintainer.

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v2024071601