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open_llama_13b

openlm-research

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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Text generation
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open_llama_3b

openlm-research

In this repo, we present a permissively licensed open source reproduction of Meta AI's LLaMA large language model. We are releasing a 7B and 3B model trained on 1T tokens, as well as the preview of a 13B model trained on 600B tokens. We provide PyTorch and JAX weights of pre-trained OpenLLaMA models, as well as evaluation results and comparison against the original LLaMA models. Please see the project homepage of OpenLLaMA for more details. We release the weights in two formats: an EasyLM format to be use with our EasyLM framework, and a PyTorch format to be used with the Hugging Face transformers library. Both our training framework EasyLM and the checkpoint weights are licensed permissively under the Apache 2.0 license. Preview checkpoints can be directly loaded from Hugging Face Hub. **Please note that it is advised to avoid using the Hugging Face fast tokenizer for now, as we’ve observed that the auto-converted fast tokenizer sometimes gives incorrect tokenizations.** This can be achieved by directly using the `LlamaTokenizer` class, or passing in the `use_fast=False` option for the `AutoTokenizer` class. See the following example for usage.

Text generation
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open_llama_3b_v2

openlm-research

**TL;DR**: we are releasing our public preview of OpenLLaMA, a permissively licensed open source reproduction of Meta AI’s LLaMA. We are releasing a series of 3B, 7B and 13B models trained on different data mixtures. Our model weights can serve as the drop in replacement of LLaMA in existing implementations. In this repo, we present a permissively licensed open source reproduction of Meta AI's LLaMA large language model. We are releasing a series of 3B, 7B and 13B models trained on 1T tokens. We provide PyTorch and JAX weights of pre-trained OpenLLaMA models, as well as evaluation results and comparison against the original LLaMA models. The v2 model is better than the old v1 model trained on a different data mixture. Please see the project homepage of OpenLLaMA for more details. We release the weights in two formats: an EasyLM format to be use with our EasyLM framework, and a PyTorch format to be used with the Hugging Face transformers library. Both our training framework EasyLM and the checkpoint weights are licensed permissively under the Apache 2.0 license.

Text generation
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