README_TEMPLATE.md

metadata

license: mit
language:
  - en
tags:
  - llm-rs
  - ggml
pipeline_tag: text-generation
datasets:
  - databricks/databricks-dolly-15k

GGML converted version of Databricks Dolly-V2 models

Description

Dolly is trained on ~15k instruction/response fine tuning records databricks-dolly-15k generated by Databricks employees in capability domains from the InstructGPT paper, including brainstorming, classification, closed QA, generation, information extraction, open QA and summarization.

Converted Models

$MODELS$

Usage

Python via llm-rs:

Installation

Via pip: pip install llm-rs

Run inference

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/dolly-v2-ggml",model_file="dolly-v2-12b-q4_0-ggjt.bin")

#Generate
print(model.generate("The meaning of life is"))

Rust via Rustformers/llm:

Installation

git clone --recurse-submodules https://github.com/rustformers/llm.git
cd llm
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:"