EraX VL 2B V1.5 Q4 K M GGUF
This model was converted to GGUF format from erax-ai/EraX-VL-2B-V1.5 using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.
Model source
- Kind
- Other
- File size
- 940 MB
- Base model
- erax-ai/EraX-VL-2B-V1.5
- Version
- vRevision 11cdc17
- Updated
- Sep 15, 2026
- Downloads
- 38
- Source
- Hugging Face
Source description
Ngoac/EraX-VL-2B-V1.5-Q4_K_M-GGUF
This model was converted to GGUF format from erax-ai/EraX-VL-2B-V1.5 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 Ngoac/EraX-VL-2B-V1.5-Q4_K_M-GGUF --hf-file erax-vl-2b-v1.5-q4_k_m.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo Ngoac/EraX-VL-2B-V1.5-Q4_K_M-GGUF --hf-file erax-vl-2b-v1.5-q4_k_m.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 Ngoac/EraX-VL-2B-V1.5-Q4_K_M-GGUF --hf-file erax-vl-2b-v1.5-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo Ngoac/EraX-VL-2B-V1.5-Q4_K_M-GGUF --hf-file erax-vl-2b-v1.5-q4_k_m.gguf -c 2048
Sources
1 source
Sources
1 sourceVerified Aug 21
Model artifacts
1 artifact
Model artifacts
1 artifactSource excerpts
2 excerpts
Source excerpts
2 excerpts--- license: apache-2.0 language: - vi - en - zh base_model: erax-ai/EraX-VL-2B-V1.5 library_name: transformers tags: - erax - multimodal - erax-vl-2B - insurance - ocr - vietnamese - bcg - llama-cpp - gguf-my-repo pipeline_tag: visual-question-answering widget: - src: images/photo-1-16505057982762025719470.webp example_title: Test 1 - src: images/vt-don-thuoc-f0-7417.jpeg example_title: Test 2 --- # Ngoac/EraX-VL-2B-V1.5-Q4_K_M-GGUF This model was converted to GGUF format from [`erax-ai/EraX-VL-2B-V1.5`](https://huggingface.co/erax-ai/EraX-VL-2B-V1.5) 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/erax-ai/EraX-VL-2B-V1.5) 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 Ngoac/EraX-VL-2B-V1.5-Q4_K_M-GGUF --hf-file erax-vl-2b-v1.5-q4_k_m.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo Ngoac/EraX-VL-2B-V1.5-Q4_K_M-GGUF --hf-file erax-vl-2b-v1.5-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 Ngoac/EraX-VL-2B-V1.5-Q4_K_M-GGUF --hf-file erax-vl-2b-v1.5-q4_k_m.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo Ngoac/EraX-VL-2B-V1.5-Q4_K_M-GGUF --hf-file erax-vl-2b-v1.5-q4_k_m.gguf -c 2048 ```
Source context: 38 downloads · 0 likes · Pipeline visual-question-answering · Library transformers · Repo Ngoac/EraX-VL-2B-V1.5-Q4_K_M-GGUF
