---
license: apache-2.0
datasets:
- FreedomIntelligence/ApolloMoEDataset
language:
- ar
- en
- zh
- ko
- ja
- mn
- th
- vi
- lo
- mg
- de
- pt
- es
- fr
- ru
- it
- hr
- gl
- cs
- co
- la
- uk
- bs
- bg
- eo
- sq
- da
- sa
- gn
- sr
- sk
- gd
- lb
- hi
- ku
- mt
- he
- ln
- bm
- sw
- ig
- rw
- ha
metrics:
- accuracy
base_model: FreedomIntelligence/Apollo2-7B
pipeline_tag: question-answering
tags:
- biology
- medical
- llama-cpp
- gguf-my-repo
---

# nchen909/Apollo2-7B-Q8_0-GGUF
This model was converted to GGUF format from [`FreedomIntelligence/Apollo2-7B`](https://huggingface.co/FreedomIntelligence/Apollo2-7B) 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/FreedomIntelligence/Apollo2-7B) 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 nchen909/Apollo2-7B-Q8_0-GGUF --hf-file apollo2-7b-q8_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo nchen909/Apollo2-7B-Q8_0-GGUF --hf-file apollo2-7b-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 nchen909/Apollo2-7B-Q8_0-GGUF --hf-file apollo2-7b-q8_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo nchen909/Apollo2-7B-Q8_0-GGUF --hf-file apollo2-7b-q8_0.gguf -c 2048
```