
This is the HuggingFace model release of the instruction tuned LLAMA-7B model used in our paper [FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation](https://arxiv.org/abs/2305.14251).

Please refer to the README for instructions on how to setup the model ([link](https://github.com/shmsw25/FActScore#download-the-data)).

Credits to [Yizhong Wang](https://homes.cs.washington.edu/~yizhongw/) for originally training this model.
{"language": ["en"], "license": "cc-by-nc-4.0", "tags": ["llama", "instruction-tuning", "large-language-model", "autoregressive", "text-generation"]}
transformers pytorch llama text-generation instruction-tuning large-language-model autoregressive en arxiv:2305.14251 license:cc-by-nc-4.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #llama #text-generation #instruction-tuning #large-language-model #autoregressive #en #arxiv-2305.14251 #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 


This is the HuggingFace model release of the instruction tuned LLAMA-7B model used in our paper FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation.

Please refer to the README for instructions on how to setup the model (link).

Credits to Yizhong Wang for originally training this model.
TAGS
#transformers #pytorch #llama #text-generation #instruction-tuning #large-language-model #autoregressive #en #arxiv-2305.14251 #license-cc-by-nc-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
