Llama 2 7B

Type: model

Tags: opensource Publisher: Meta Released: 2023-07-19 v.1.0.0

Metadata

General information.

name: Llama 2 7B
version: 1.0.0
publisher: Meta
model type: Large Language Model
release date: 2023-07-19
description: This is the 7B variant.
architecture: Llama 2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.

Llama 2 is intended for commercial and research use in English.
Tuned models are intended for assistant-like chat.
Pretrained models can be adapted for a variety of natural language generation tasks.
Developers may fine-tune Llama 2 models for languages beyond English provided they comply with the Llama 2 Community License and the Acceptable Use Policy.
Use in any manner that violates applicable laws or regulations is out-of-scope.

Range of parameter sizes — 7B, 13B, and 70B — as well as pretrained and fine-tuned variations.
Input text only.
Output text only.
Model architecture uses an optimized transformer architecture.
Models are trained with a global batch-size of 4M tokens.

Evaluation data includes standard academic benchmarks across commonsense reasoning, world knowledge, reading comprehension, and math.
Automatic safety benchmarks such as TruthfulQA and ToxiGen for evaluating truthfulness and toxicity.
The BOLD dataset for measuring biases in open-ended language generation.
Use of internal evaluations library for consistency across evaluations.
Both pretrained Llama 2 and fine-tuned Llama 2-Chat models are evaluated on these benchmarks.

2 trillion tokens of data from publicly available sources were used for pretraining.
Fine-tuning data includes publicly available instruction datasets, as well as over one million new human-annotated examples.
The pretraining data has a cutoff of September 2022, but some tuning data is more recent, up to July 2023.
Neither the pretraining nor the fine-tuning datasets include Meta user data.
A new mix of publicly available online data was curated for the training process.

The 70B version uses Grouped-Query Attention (GQA) for improved inference scalability.
Token counts refer to pretraining data only.
The models were trained between January 2023 and July 2023.
A custom commercial license is available for use.
More detailed information can be found in the research paper "Llama-2: Open Foundation and Fine-tuned Chat Models".

Before deploying any applications of Llama 2, developers should perform safety testing and tuning tailored to specific applications.
Consult the Responsible Use Guide available on Meta AI's website.
Regular updating and fine-tuning with newer data and community feedback is recommended to improve model safety and effectiveness.
Consider language variations and cultural contexts when adapting Llama 2 models for languages beyond English.
Stay informed about updates to model versions and licenses.