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AI Model Library/princeton-nlp/Sheared-LLaMA-1.3B
MODEL PROFILE

Sheared-LLaMA-1.3B

princeton-nlp · Sheared-LLaMA-1.3B

**Paper**: https://arxiv.org/pdf/2310.06694.pdf **Code**: https://github.com/princeton-nlp/LLM-Shearing **Models**: Sheared-LLaMA-1.3B, Sheared-LLaMA-2.7B **Pruned Models without Continued Pre-training**: Sheared-LLaMA-1.3B-Pruned, Sheared-LLaMA-2.7B-Pruned **Instruction-tuned Models**: Sheared-LLaMA-1.3B-ShareGPT, Sheared-LLaMA-2.7B-ShareGPT Sheared-LLaMA-1.3B is a model pruned and further pre-trained from meta-llama/Llama-2-7b-hf. We dynamically load data from different domains in the RedPajama dataset to prune and contune pre-train the model. We use 0.4B tokens for pruning and 50B tokens for continued pre-training the pruned model. This model can be loaded with HuggingFace via We evaluate on an extensive set of downstream tasks including reasoning, reading comprehension, language modeling and knowledge intensive tasks. Our Sheared-LLaMA models outperform existing large language models.

Text generationlicense:apache-2.0
Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/11/2 19:16:21
OVERVIEW

Model overview

**Paper**: https://arxiv.org/pdf/2310.06694.pdf **Code**: https://github.com/princeton-nlp/LLM-Shearing **Models**: Sheared-LLaMA-1.3B, Sheared-LLaMA-2.7B **Pruned Models without Continued Pre-training**: Sheared-LLaMA-1.3B-Pruned, Sheared-LLaMA-2.7B-Pruned **Instruction-tuned Models**: Sheared-LLaMA-1.3B-ShareGPT, Sheared-LLaMA-2.7B-ShareGPT Sheared-LLaMA-1.3B is a model pruned and further pre-trained from meta-llama/Llama-2-7b-hf. We dynamically load data from different domains in the RedPajama dataset to prune and contune pre-train the model. We use 0.4B tokens for pruning and 50B tokens for continued pre-training the pruned model. This model can be loaded with HuggingFace via We evaluate on an extensive set of downstream tasks including reasoning, reading comprehension, language modeling and knowledge intensive tasks. Our Sheared-LLaMA models outperform existing large language models.

Key features

特点摘要待依据来源补齐，不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

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Frequently asked questions

Do open weights permit free commercial use?

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Sources & traceability

huggingface · princeton-nlp/Sheared-LLaMA-1.3B ↗2026/10/30 17:37:07
huggingface · enrich:d7443c61-d839-4148-a13f-afd912ba0ce3 ↗2026/10/31 08:41:13

许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。