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license: other
datasets:
- tiiuae/falcon-refinedweb
- bigcode/the-stack-github-issues
- bigcode/commitpackft
- bigcode/starcoderdata
- EleutherAI/proof-pile-2
- meta-math/MetaMathQA
language:
- en
tags:
- causal-lm
- code
- llama-cpp
- gguf-my-repo
metrics:
- code_eval
library_name: transformers
base_model: stabilityai/stable-code-3b
model-index:
- name: stabilityai/stable-code-3b
results:
- task:
type: text-generation
dataset:
name: MultiPL-HumanEval (Python)
type: nuprl/MultiPL-E
metrics:
- type: pass@1
value: 32.4
name: pass@1
verified: false
- type: pass@1
value: 30.9
name: pass@1
verified: false
- type: pass@1
value: 32.1
name: pass@1
verified: false
- type: pass@1
value: 32.1
name: pass@1
verified: false
- type: pass@1
value: 24.2
name: pass@1
verified: false
- type: pass@1
value: 23.0
name: pass@1
verified: false
---
# devisri050/stable-code-3b-Q8_0-GGUF
This model was converted to GGUF format from [`stabilityai/stable-code-3b`](https://huggingface.co/stabilityai/stable-code-3b) 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/stabilityai/stable-code-3b) 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 devisri050/stable-code-3b-Q8_0-GGUF --hf-file stable-code-3b-q8_0.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo devisri050/stable-code-3b-Q8_0-GGUF --hf-file stable-code-3b-q8_0.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 devisri050/stable-code-3b-Q8_0-GGUF --hf-file stable-code-3b-q8_0.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo devisri050/stable-code-3b-Q8_0-GGUF --hf-file stable-code-3b-q8_0.gguf -c 2048
```
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