Instructions to use Lamapi/next-ocr-Q5_K_M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Lamapi/next-ocr-Q5_K_M-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="Lamapi/next-ocr-Q5_K_M-GGUF")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Lamapi/next-ocr-Q5_K_M-GGUF", dtype="auto")

llama-cpp-python

How to use Lamapi/next-ocr-Q5_K_M-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Lamapi/next-ocr-Q5_K_M-GGUF",
	filename="next-ocr-q5_k_m.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Lamapi/next-ocr-Q5_K_M-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Lamapi/next-ocr-Q5_K_M-GGUF:Q5_K_M
# Run inference directly in the terminal:
llama-cli -hf Lamapi/next-ocr-Q5_K_M-GGUF:Q5_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Lamapi/next-ocr-Q5_K_M-GGUF:Q5_K_M
# Run inference directly in the terminal:
llama-cli -hf Lamapi/next-ocr-Q5_K_M-GGUF:Q5_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf Lamapi/next-ocr-Q5_K_M-GGUF:Q5_K_M
# Run inference directly in the terminal:
./llama-cli -hf Lamapi/next-ocr-Q5_K_M-GGUF:Q5_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf Lamapi/next-ocr-Q5_K_M-GGUF:Q5_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Lamapi/next-ocr-Q5_K_M-GGUF:Q5_K_M

Use Docker

docker model run hf.co/Lamapi/next-ocr-Q5_K_M-GGUF:Q5_K_M

LM Studio
Jan

vLLM

How to use Lamapi/next-ocr-Q5_K_M-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Lamapi/next-ocr-Q5_K_M-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Lamapi/next-ocr-Q5_K_M-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Lamapi/next-ocr-Q5_K_M-GGUF:Q5_K_M

SGLang

How to use Lamapi/next-ocr-Q5_K_M-GGUF with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Lamapi/next-ocr-Q5_K_M-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Lamapi/next-ocr-Q5_K_M-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Lamapi/next-ocr-Q5_K_M-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Lamapi/next-ocr-Q5_K_M-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Ollama
How to use Lamapi/next-ocr-Q5_K_M-GGUF with Ollama:
```
ollama run hf.co/Lamapi/next-ocr-Q5_K_M-GGUF:Q5_K_M
```

Unsloth Studio

How to use Lamapi/next-ocr-Q5_K_M-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Lamapi/next-ocr-Q5_K_M-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Lamapi/next-ocr-Q5_K_M-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Lamapi/next-ocr-Q5_K_M-GGUF to start chatting

Docker Model Runner
How to use Lamapi/next-ocr-Q5_K_M-GGUF with Docker Model Runner:
```
docker model run hf.co/Lamapi/next-ocr-Q5_K_M-GGUF:Q5_K_M
```

Lemonade

How to use Lamapi/next-ocr-Q5_K_M-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Lamapi/next-ocr-Q5_K_M-GGUF:Q5_K_M

Run and chat with the model

lemonade run user.next-ocr-Q5_K_M-GGUF-Q5_K_M

List all available models

lemonade list

Lamapi commited on Nov 13, 2025

Commit

d86a231

verified ·

1 Parent(s): 3e9a75c

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+---
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- qwen3_vl
+- trl
+- sft
+- chemistry
+- code
+- climate
+- art
+- biology
+- finance
+- legal
+- music
+- medical
+- agent
+- llama-cpp
+- gguf-my-repo
+license: apache-2.0
+language:
+- en
+- ab
+- aa
+- ae
+- af
+- ak
+- am
+- an
+- ar
+- as
+- av
+- ay
+- az
+- ba
+- be
+- bg
+- bh
+- bi
+- bm
+- bn
+- bo
+- br
+- bs
+- ca
+- ce
+- ch
+- co
+- cr
+- cs
+- cu
+- cv
+- cy
+- da
+- de
+- dv
+- dz
+- ee
+- el
+- eo
+- es
+- et
+- eu
+- fa
+- ff
+- fi
+- fj
+- fo
+- fr
+- fy
+- ga
+- gd
+- gl
+- gn
+- gv
+- ha
+- he
+- hi
+- ho
+- gu
+- hr
+- ht
+- hu
+- hz
+- hy
+- id
+- ia
+- ig
+- ie
+- ik
+- ii
+- is
+- io
+- iu
+- it
+- jv
+- ja
+- kg
+- ka
+- kj
+- ki
+- kl
+- kk
+- kn
+- km
+- kr
+- ko
+- ku
+- ks
+- kw
+- kv
+- la
+- ky
+- lg
+- lb
+- ln
+- li
+- lt
+- lo
+- lv
+- lu
+- mg
+- mi
+- mh
+- ml
+- mk
+- mr
+- mn
+- mt
+- ms
+- na
+- my
+- nd
+- nb
+- ng
+- nl
+- ne
+- 'no'
+- nn
+- nv
+- nr
+- oc
+- oj
+- om
+- ny
+- os
+- or
+- pa
+- pi
+- pl
+- ps
+- pt
+- rm
+- rn
+- qu
+- ro
+- ru
+- sn
+- rw
+- so
+- sa
+- sc
+- sd
+pipeline_tag: image-text-to-text
+library_name: transformers
+base_model: Lamapi/next-ocr
+---
+# Lamapi/next-ocr-Q5_K_M-GGUF
+This model was converted to GGUF format from [`Lamapi/next-ocr`](https://huggingface.co/Lamapi/next-ocr) 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/Lamapi/next-ocr) 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 Lamapi/next-ocr-Q5_K_M-GGUF --hf-file next-ocr-q5_k_m.gguf -p "The meaning to life and the universe is"
+```
+### Server:
+```bash
+llama-server --hf-repo Lamapi/next-ocr-Q5_K_M-GGUF --hf-file next-ocr-q5_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 Lamapi/next-ocr-Q5_K_M-GGUF --hf-file next-ocr-q5_k_m.gguf -p "The meaning to life and the universe is"
+```
+or
+```
+./llama-server --hf-repo Lamapi/next-ocr-Q5_K_M-GGUF --hf-file next-ocr-q5_k_m.gguf -c 2048
+```