README.md

---
license: apache-2.0
library_name: transformers
tags:
- code
- granite
- llama-cpp
- gguf-my-repo
base_model: ibm-granite/granite-8b-code-base
datasets:
- bigcode/commitpackft
- TIGER-Lab/MathInstruct
- meta-math/MetaMathQA
- glaiveai/glaive-code-assistant-v3
- glaive-function-calling-v2
- bugdaryan/sql-create-context-instruction
- garage-bAInd/Open-Platypus
- nvidia/HelpSteer
metrics:
- code_eval
pipeline_tag: text-generation
inference: false
model-index:
- name: granite-8b-code-instruct
  results:
  - task:
      type: text-generation
    dataset:
      name: HumanEvalSynthesis(Python)
      type: bigcode/humanevalpack
    metrics:
    - type: pass@1
      value: 57.9
      name: pass@1
    - type: pass@1
      value: 52.4
      name: pass@1
    - type: pass@1
      value: 58.5
      name: pass@1
    - type: pass@1
      value: 43.3
      name: pass@1
    - type: pass@1
      value: 48.2
      name: pass@1
    - type: pass@1
      value: 37.2
      name: pass@1
    - type: pass@1
      value: 53.0
      name: pass@1
    - type: pass@1
      value: 42.7
      name: pass@1
    - type: pass@1
      value: 52.4
      name: pass@1
    - type: pass@1
      value: 36.6
      name: pass@1
    - type: pass@1
      value: 43.9
      name: pass@1
    - type: pass@1
      value: 16.5
      name: pass@1
    - type: pass@1
      value: 39.6
      name: pass@1
    - type: pass@1
      value: 40.9
      name: pass@1
    - type: pass@1
      value: 48.2
      name: pass@1
    - type: pass@1
      value: 41.5
      name: pass@1
    - type: pass@1
      value: 39.0
      name: pass@1
    - type: pass@1
      value: 32.9
      name: pass@1
---

# MoMonir/granite-8b-code-instruct-GGUF
This model was converted to GGUF format from [`ibm-granite/granite-8b-code-instruct`](https://huggingface.co/ibm-granite/granite-8b-code-instruct) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/ibm-granite/granite-8b-code-instruct) for more details on the model.


<!-- README_GGUF.md-about-gguf start -->
### About GGUF ([TheBloke](https://huggingface.co/TheBloke) Description)

GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp.

Here is an incomplete list of clients and libraries that are known to support GGUF:

* [llama.cpp](https://github.com/ggerganov/llama.cpp). The source project for GGUF. Offers a CLI and a server option.
* [text-generation-webui](https://github.com/oobabooga/text-generation-webui), the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration.
* [KoboldCpp](https://github.com/LostRuins/koboldcpp), a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling.
* [GPT4All](https://gpt4all.io/index.html), a free and open source local running GUI, supporting Windows, Linux and macOS with full GPU accel.
* [LM Studio](https://lmstudio.ai/), an easy-to-use and powerful local GUI for Windows and macOS (Silicon), with GPU acceleration. Linux available, in beta as of 27/11/2023.
* [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui), a great web UI with many interesting and unique features, including a full model library for easy model selection.
* [Faraday.dev](https://faraday.dev/), an attractive and easy to use character-based chat GUI for Windows and macOS (both Silicon and Intel), with GPU acceleration.
* [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), a Python library with GPU accel, LangChain support, and OpenAI-compatible API server.
* [candle](https://github.com/huggingface/candle), a Rust ML framework with a focus on performance, including GPU support, and ease of use.
* [ctransformers](https://github.com/marella/ctransformers), a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server. Note, as of time of writing (November 27th 2023), ctransformers has not been updated in a long time and does not support many recent models.

<!-- README_GGUF.md-about-gguf end -->

## Use with llama.cpp

Install llama.cpp through brew.

```bash
brew install ggerganov/ggerganov/llama.cpp
```
Invoke the llama.cpp server or the CLI.

CLI:

```bash
llama-cli --hf-repo MoMonir/granite-8b-code-instruct-GGUF --model granite-8b-code-instruct.Q4_K_M.gguf -p "The meaning to life and the universe is"
```

Server:

```bash
llama-server --hf-repo MoMonir/granite-8b-code-instruct-GGUF --model granite-8b-code-instruct.Q4_K_M.gguf -c 2048
```

Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.

```
git clone https://github.com/ggerganov/llama.cpp &&             cd llama.cpp &&             make &&             ./main -m granite-8b-code-instruct.Q4_K_M.gguf -n 128
```