File size: 2,245 Bytes
3dea944 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 |
---
base_model: HPAI-BSC/Llama3-Aloe-8B-Alpha
datasets:
- argilla/dpo-mix-7k
- nvidia/HelpSteer
- jondurbin/airoboros-3.2
- hkust-nlp/deita-10k-v0
- LDJnr/Capybara
- HPAI-BSC/CareQA
- GBaker/MedQA-USMLE-4-options
- lukaemon/mmlu
- bigbio/pubmed_qa
- openlifescienceai/medmcqa
- bigbio/med_qa
- HPAI-BSC/better-safe-than-sorry
- HPAI-BSC/pubmedqa-cot
- HPAI-BSC/medmcqa-cot
- HPAI-BSC/medqa-cot
language:
- en
library_name: transformers
license: cc-by-nc-4.0
pipeline_tag: question-answering
tags:
- biology
- medical
- llama-cpp
- gguf-my-repo
---
# codegood/Llama3-Aloe-8B-Alpha-Q4_K_M-GGUF
This model was converted to GGUF format from [`HPAI-BSC/Llama3-Aloe-8B-Alpha`](https://huggingface.co/HPAI-BSC/Llama3-Aloe-8B-Alpha) 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/HPAI-BSC/Llama3-Aloe-8B-Alpha) 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 codegood/Llama3-Aloe-8B-Alpha-Q4_K_M-GGUF --hf-file llama3-aloe-8b-alpha-q4_k_m.gguf -p "The meaning to life and the universe is"
```
### Server:
```bash
llama-server --hf-repo codegood/Llama3-Aloe-8B-Alpha-Q4_K_M-GGUF --hf-file llama3-aloe-8b-alpha-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.
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 codegood/Llama3-Aloe-8B-Alpha-Q4_K_M-GGUF --hf-file llama3-aloe-8b-alpha-q4_k_m.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo codegood/Llama3-Aloe-8B-Alpha-Q4_K_M-GGUF --hf-file llama3-aloe-8b-alpha-q4_k_m.gguf -c 2048
```
|