README.md

---
base_model: bigcode/starcoder2-15b
datasets:
- bigcode/the-stack-v2-train
library_name: transformers
license: bigcode-openrail-m
pipeline_tag: text-generation
tags:
- code
- llama-cpp
- gguf-my-repo
inference:
  parameters:
    temperature: 0.2
    top_p: 0.95
widget:
- text: 'def print_hello_world():'
  example_title: Hello world
  group: Python
model-index:
- name: starcoder2-15b
  results:
  - task:
      type: text-generation
    dataset:
      name: CruxEval-I
      type: cruxeval-i
    metrics:
    - type: pass@1
      value: 48.1
  - task:
      type: text-generation
    dataset:
      name: DS-1000
      type: ds-1000
    metrics:
    - type: pass@1
      value: 33.8
  - task:
      type: text-generation
    dataset:
      name: GSM8K (PAL)
      type: gsm8k-pal
    metrics:
    - type: accuracy
      value: 65.1
  - task:
      type: text-generation
    dataset:
      name: HumanEval+
      type: humanevalplus
    metrics:
    - type: pass@1
      value: 37.8
  - task:
      type: text-generation
    dataset:
      name: HumanEval
      type: humaneval
    metrics:
    - type: pass@1
      value: 46.3
  - task:
      type: text-generation
    dataset:
      name: RepoBench-v1.1
      type: repobench-v1.1
    metrics:
    - type: edit-smiliarity
      value: 74.08
---

# Ffftdtd5dtft/starcoder2-15b-Q2_K-GGUF
This model was converted to GGUF format from [`bigcode/starcoder2-15b`](https://huggingface.co/bigcode/starcoder2-15b) 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/bigcode/starcoder2-15b) for more details on the model.

## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo Ffftdtd5dtft/starcoder2-15b-Q2_K-GGUF --hf-file starcoder2-15b-q2_k.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Ffftdtd5dtft/starcoder2-15b-Q2_K-GGUF --hf-file starcoder2-15b-q2_k.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.

Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```

Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```

Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo Ffftdtd5dtft/starcoder2-15b-Q2_K-GGUF --hf-file starcoder2-15b-q2_k.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Ffftdtd5dtft/starcoder2-15b-Q2_K-GGUF --hf-file starcoder2-15b-q2_k.gguf -c 2048
```