c41n3/open_llama_3b_v2-Q8_0-GGUF overview
c41n3/open llama 3b v2 Q8 0 GGUF This model was converted to GGUF format from openlm research/open llama 3b v2 https://huggingface.co/openlm research/open llam…
Runs locally from ~3.39 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| open_llama_3b_v2-q8_0.gguf | GGUF | Q8_0 | 3.39 GB | Download |
Model Details
Model README
---
license: apache-2.0
datasets:
- tiiuae/falcon-refinedweb
- bigcode/starcoderdata
- togethercomputer/RedPajama-Data-1T
base_model: openlm-research/open_llama_3b_v2
tags:
- llama-cpp
- gguf-my-repo
---
c41n3/open_llama_3b_v2-Q8_0-GGUF
This model was converted to GGUF format from openlm-research/open_llama_3b_v2 using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo c41n3/open_llama_3b_v2-Q8_0-GGUF --hf-file open_llama_3b_v2-q8_0.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo c41n3/open_llama_3b_v2-Q8_0-GGUF --hf-file open_llama_3b_v2-q8_0.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps 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 c41n3/open_llama_3b_v2-Q8_0-GGUF --hf-file open_llama_3b_v2-q8_0.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo c41n3/open_llama_3b_v2-Q8_0-GGUF --hf-file open_llama_3b_v2-q8_0.gguf -c 2048Run c41n3/open_llama_3b_v2-Q8_0-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models