
# 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
| Name                                                                                                                | Based on                                                                  | Type   | Container   | GGML Version   |
|:--------------------------------------------------------------------------------------------------------------------|:--------------------------------------------------------------------------|:-------|:------------|:---------------|
| [dolly-v2-12b-f16.bin](https://huggingface.co/rustformers/dolly-v2-ggml/blob/main/dolly-v2-12b-f16.bin)             | [databricks/dolly-v2-12b](https://huggingface.co/databricks/dolly-v2-12b) | F16    | GGML        | V3             |
| [dolly-v2-12b-q4_0.bin](https://huggingface.co/rustformers/dolly-v2-ggml/blob/main/dolly-v2-12b-q4_0.bin)           | [databricks/dolly-v2-12b](https://huggingface.co/databricks/dolly-v2-12b) | Q4_0   | GGML        | V3             |
| [dolly-v2-12b-q4_0-ggjt.bin](https://huggingface.co/rustformers/dolly-v2-ggml/blob/main/dolly-v2-12b-q4_0-ggjt.bin) | [databricks/dolly-v2-12b](https://huggingface.co/databricks/dolly-v2-12b) | Q4_0   | GGJT        | V3             |
| [dolly-v2-3b-f16.bin](https://huggingface.co/rustformers/dolly-v2-ggml/blob/main/dolly-v2-3b-f16.bin)               | [databricks/dolly-v2-3b](https://huggingface.co/databricks/dolly-v2-3b)   | F16    | GGML        | V3             |
| [dolly-v2-3b-q4_0.bin](https://huggingface.co/rustformers/dolly-v2-ggml/blob/main/dolly-v2-3b-q4_0.bin)             | [databricks/dolly-v2-3b](https://huggingface.co/databricks/dolly-v2-3b)   | Q4_0   | GGML        | V3             |
| [dolly-v2-3b-q4_0-ggjt.bin](https://huggingface.co/rustformers/dolly-v2-ggml/blob/main/dolly-v2-3b-q4_0-ggjt.bin)   | [databricks/dolly-v2-3b](https://huggingface.co/databricks/dolly-v2-3b)   | Q4_0   | GGJT        | V3             |
| [dolly-v2-3b-q5_1.bin](https://huggingface.co/rustformers/dolly-v2-ggml/blob/main/dolly-v2-3b-q5_1.bin)             | [databricks/dolly-v2-3b](https://huggingface.co/databricks/dolly-v2-3b)   | Q5_1   | GGML        | V3             |
| [dolly-v2-3b-q5_1-ggjt.bin](https://huggingface.co/rustformers/dolly-v2-ggml/blob/main/dolly-v2-3b-q5_1-ggjt.bin)   | [databricks/dolly-v2-3b](https://huggingface.co/databricks/dolly-v2-3b)   | Q5_1   | GGJT        | V3             |
| [dolly-v2-7b-f16.bin](https://huggingface.co/rustformers/dolly-v2-ggml/blob/main/dolly-v2-7b-f16.bin)               | [databricks/dolly-v2-7b](https://huggingface.co/databricks/dolly-v2-7b)   | F16    | GGML        | V3             |
| [dolly-v2-7b-q4_0.bin](https://huggingface.co/rustformers/dolly-v2-ggml/blob/main/dolly-v2-7b-q4_0.bin)             | [databricks/dolly-v2-7b](https://huggingface.co/databricks/dolly-v2-7b)   | Q4_0   | GGML        | V3             |
| [dolly-v2-7b-q4_0-ggjt.bin](https://huggingface.co/rustformers/dolly-v2-ggml/blob/main/dolly-v2-7b-q4_0-ggjt.bin)   | [databricks/dolly-v2-7b](https://huggingface.co/databricks/dolly-v2-7b)   | Q4_0   | GGJT        | V3             |
| [dolly-v2-7b-q5_1.bin](https://huggingface.co/rustformers/dolly-v2-ggml/blob/main/dolly-v2-7b-q5_1.bin)             | [databricks/dolly-v2-7b](https://huggingface.co/databricks/dolly-v2-7b)   | Q5_1   | GGML        | V3             |
| [dolly-v2-7b-q5_1-ggjt.bin](https://huggingface.co/rustformers/dolly-v2-ggml/blob/main/dolly-v2-7b-q5_1-ggjt.bin)   | [databricks/dolly-v2-7b](https://huggingface.co/databricks/dolly-v2-7b)   | Q5_1   | GGJT        | V3             |

## 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:"
```
{"language": ["en"], "license": "mit", "tags": ["llm-rs", "ggml"], "datasets": ["databricks/databricks-dolly-15k"], "pipeline_tag": "text-generation"}
transformers gpt_neox llm-rs ggml text-generation en dataset:databricks/databricks-dolly-15k license:mit endpoints_compatible text-generation-inference region:us
TAGS
#transformers #gpt_neox #llm-rs #ggml #text-generation #en #dataset-databricks/databricks-dolly-15k #license-mit #endpoints_compatible #text-generation-inference #region-us 

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
----------------



Usage
-----


### Python via llm-rs:


#### Installation


Via pip: 'pip install llm-rs'


#### Run inference


### Rust via Rustformers/llm:


#### Installation


#### Run inference



### Python via llm-rs: #### Installation


Via pip: 'pip install llm-rs' #### Run inference ### Rust via Rustformers/llm: #### Installation #### Run inference
TAGS
#transformers #gpt_neox #llm-rs #ggml #text-generation #en #dataset-databricks/databricks-dolly-15k #license-mit #endpoints_compatible #text-generation-inference #region-us 
 ### Python via llm-rs: #### Installation


Via pip: 'pip install llm-rs' #### Run inference ### Rust via Rustformers/llm: #### Installation #### Run inference