README_TEMPLATE.md

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

# GGML converted version of [Databricks](https://huggingface.co/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](https://github.com/LLukas22/llm-rs-python):

#### Installation
Via pip: `pip install llm-rs`

#### Run inference
```python
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](https://github.com/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:"
```