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
| Name | Based on | Type | Container | GGML Version |
|---|---|---|---|---|
| dolly-v2-12b-f16.bin | databricks/dolly-v2-12b | F16 | GGML | V3 |
| dolly-v2-12b-q4_0.bin | databricks/dolly-v2-12b | Q4_0 | GGML | V3 |
| dolly-v2-12b-q4_0-ggjt.bin | databricks/dolly-v2-12b | Q4_0 | GGJT | V3 |
| dolly-v2-3b-f16.bin | databricks/dolly-v2-3b | F16 | GGML | V3 |
| dolly-v2-3b-q4_0.bin | databricks/dolly-v2-3b | Q4_0 | GGML | V3 |
| dolly-v2-3b-q4_0-ggjt.bin | databricks/dolly-v2-3b | Q4_0 | GGJT | V3 |
| dolly-v2-3b-q5_1-ggjt.bin | databricks/dolly-v2-3b | Q5_1 | GGJT | V3 |
| dolly-v2-7b-f16.bin | databricks/dolly-v2-7b | F16 | GGML | V3 |
| dolly-v2-7b-q4_0.bin | databricks/dolly-v2-7b | Q4_0 | GGML | V3 |
| dolly-v2-7b-q4_0-ggjt.bin | databricks/dolly-v2-7b | Q4_0 | GGJT | V3 |
| dolly-v2-7b-q5_1-ggjt.bin | databricks/dolly-v2-7b | Q5_1 | GGJT | V3 |
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:"