Update README_TEMPLATE.md

README_TEMPLATE.md

@@ -9,24 +9,17 @@ language:
 datasets:
 - togethercomputer/RedPajama-Data-1T
 ---
-# GGML converted versions of [Together](https://huggingface.co/togethercomputer)'s RedPajama models
+# GGML converted versions of [OpenLM Research](https://huggingface.co/openlm-research)'s LLaMA models
 
-# RedPajama-INCITE-7B-Base
+# OpenLLaMA: An Open Reproduction of LLaMA
 
-RedPajama-INCITE-7B-Base was developed by Together and leaders from the open-source AI community including Ontocord.ai, ETH DS3Lab, AAI CERC, Université de Montréal, MILA - Québec AI Institute, Stanford Center for Research on Foundation Models (CRFM), Stanford Hazy Research research group and LAION. 
-The training was done on 3,072 V100 GPUs provided as part of the INCITE 2023 project on Scalable Foundation Models for Transferrable Generalist AI, awarded to MILA, LAION, and EleutherAI in fall 2022, with support from the Oak Ridge Leadership Computing Facility (OLCF) and INCITE program. 
 
-  - Base Model: [RedPajama-INCITE-7B-Base](https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Base)
-  - Instruction-tuned Version: [RedPajama-INCITE-7B-Instruct](https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Instruct)
-  - Chat Version: [RedPajama-INCITE-7B-Chat](https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Chat)
+In this repo, we present a permissively licensed open source reproduction of Meta AI's [LLaMA](https://ai.facebook.com/blog/large-language-model-llama-meta-ai/) 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](https://github.com/openlm-research/open_llama) for more details.
 
 
-## Model Details
-- **Developed by**: Together Computer.
-- **Model type**: Language Model
-- **Language(s)**: English
-- **License**: Apache 2.0
-- **Model Description**: A 6.9B parameter pretrained language model.
+## Weights Release, License and Usage
+
+We release the weights in two formats: an EasyLM format to be use with our [EasyLM framework](https://github.com/young-geng/EasyLM), and a PyTorch format to be used with the [Hugging Face transformers](https://huggingface.co/docs/transformers/index) library. Both our training framework EasyLM and the checkpoint weights are licensed permissively under the Apache 2.0 license.
 
 ## Converted Models:
 
@@ -44,7 +37,7 @@ Via pip: `pip install llm-rs`
 from llm_rs import AutoModel
 
 #Load the model, define any model you like from the list above as the `model_file`
-model = AutoModel.from_pretrained("rustformers/redpajama-7b-ggml",model_file="RedPajama-INCITE-7B-Base-q4_0-ggjt.bin")
+model = AutoModel.from_pretrained("rustformers/open-llama-ggml",model_file=" open_llama_7b-q4_0-ggjt.bin")
 
 #Generate
 print(model.generate("The meaning of life is"))
@@ -68,5 +61,5 @@ cargo build --release
 
 #### Run inference
 ```
-cargo run --release -- gptneox infer -m path/to/model.bin  -p "Tell me how cool the Rust programming language is:"
+cargo run --release -- llama infer -m path/to/model.bin  -p "Tell me how cool the Rust programming language is:"
 ```