Instructions to use saidutta69/clef-flash-heretic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use saidutta69/clef-flash-heretic with Transformers:

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

pipe = pipeline("image-text-to-text", model="saidutta69/clef-flash-heretic")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("saidutta69/clef-flash-heretic")
model = AutoModelForMultimodalLM.from_pretrained("saidutta69/clef-flash-heretic", device_map="auto")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use saidutta69/clef-flash-heretic with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf saidutta69/clef-flash-heretic:F16
# Run inference directly in the terminal:
llama cli -hf saidutta69/clef-flash-heretic:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf saidutta69/clef-flash-heretic:F16
# Run inference directly in the terminal:
llama cli -hf saidutta69/clef-flash-heretic:F16

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf saidutta69/clef-flash-heretic:F16
# Run inference directly in the terminal:
./build/bin/llama cli -hf saidutta69/clef-flash-heretic:F16

Use Docker

docker model run hf.co/saidutta69/clef-flash-heretic:F16

Llama new
LM Studio
Jan

vLLM

How to use saidutta69/clef-flash-heretic with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "saidutta69/clef-flash-heretic"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "saidutta69/clef-flash-heretic",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/saidutta69/clef-flash-heretic:F16

SGLang

How to use saidutta69/clef-flash-heretic 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 "saidutta69/clef-flash-heretic" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "saidutta69/clef-flash-heretic",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "saidutta69/clef-flash-heretic" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "saidutta69/clef-flash-heretic",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Ollama
How to use saidutta69/clef-flash-heretic with Ollama:
```
ollama run hf.co/saidutta69/clef-flash-heretic:F16
```
Unsloth Desktop

How to use saidutta69/clef-flash-heretic with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf saidutta69/clef-flash-heretic:F16

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "saidutta69/clef-flash-heretic:F16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use saidutta69/clef-flash-heretic with Docker Model Runner:
```
docker model run hf.co/saidutta69/clef-flash-heretic:F16
```

Lemonade

How to use saidutta69/clef-flash-heretic with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull saidutta69/clef-flash-heretic:F16

Run and chat with the model

lemonade run user.clef-flash-heretic-F16

List all available models

lemonade list

Hermes Agent

How to use saidutta69/clef-flash-heretic with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf saidutta69/clef-flash-heretic:F16

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default saidutta69/clef-flash-heretic:F16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use saidutta69/clef-flash-heretic with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf saidutta69/clef-flash-heretic:F16

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "saidutta69/clef-flash-heretic:F16" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

saidutta69 commited on Oct 4

Commit

eea32c3

verified ·

1 Parent(s): 5f44f66

Upload reproduce/requirements.txt with huggingface_hub

Browse files

Files changed (1) hide show

reproduce/requirements.txt +109 -0

reproduce/requirements.txt ADDED Viewed

	@@ -0,0 +1,109 @@

+absl-py==2.3.1
+accelerate==1.15.0
+alembic==1.20.0
+annotated-doc==0.0.5
+annotated-types==0.8.0
+anyio==4.15.1
+bitsandbytes==0.50.2
+certifi==2025.4.26
+chardet==5.2.0
+charset-normalizer==3.4.2
+click==8.5.0
+cloudpickle==3.1.2
+colorama==0.4.6
+colorlog==6.12.0
+cuda-bindings==13.4.3
+cuda-pathfinder==1.8.3
+cuda-toolkit==13.0.3.0
+dataproperty==1.1.1
+datasets==4.8.5
+defusedxml==0.7.1
+dill==0.4.1
+evaluate==0.4.6
+exceptiongroup==1.3.0
+filelock==3.18.0
+fsspec==2025.5.1
+h11==0.16.0
+heretic-llm==1.4.0
+hf-xet==1.6.0
+httpcore==1.0.9
+httpx==0.28.1
+huggingface-hub==1.33.0
+idna==3.20
+immutabledict==4.3.1
+jinja2==3.1.6
+joblib==1.6.0
+langdetect==1.0.9
+lm-eval==0.4.13
+lxml==6.1.3
+mako==1.4.3
+markdown-it-py==4.2.0
+markupsafe==3.0.2
+mbstrdecoder==1.1.5
+mdurl==0.1.2
+more-itertools==11.1.0
+mpmath==1.3.0
+multiprocess==0.70.19
+narwhals==2.26.0
+networkx==3.5
+nltk==3.10.3
+numpy==2.2.6
+nvidia-cublas==13.1.1.3
+nvidia-cuda-nvrtc==13.0.88
+nvidia-cudnn-cu13==9.24.0.43
+nvidia-cusparselt-cu13==0.8.1
+nvidia-nccl-cu13==2.30.7
+nvidia-nvshmem-cu13==3.4.5
+optuna==4.9.0
+packaging==25.0
+pandas==3.0.6
+pathvalidate==3.3.1
+peft==0.21.2
+pillow==11.0.0
+portalocker==4.4.0
+prompt-toolkit==3.0.51
+psutil==7.2.2
+py-cpuinfo==9.0.0
+pyarrow==25.0.1
+pydantic==2.13.5
+pydantic-core==2.46.5
+pydantic-settings==2.15.0
+pygments==2.19.1
+pytablewriter==1.2.1
+python-dateutil==2.9.0.post0
+python-dotenv==1.2.4
+pyyaml==6.0.2
+questionary==2.1.1
+regex==2026.9.29
+requests==2.32.3
+rich==14.3.4
+rouge-score==0.1.2
+sacrebleu==2.6.0
+safetensors==0.8.0
+scikit-learn==1.9.1
+scipy==1.17.1
+setuptools==84.0.0
+shellingham==1.5.4
+six==1.17.0
+sqlalchemy==2.1.3
+sqlitedict==2.1.0
+sympy==1.14.0
+tabledata==1.3.5
+tabulate==0.10.0
+tcolorpy==0.1.7
+threadpoolctl==3.7.0
+tokenizers==0.23.2
+tomli-w==1.2.0
+torch==2.14.1
+torchvision==0.29.1
+tqdm==4.67.1
+transformers==5.18.0
+triton==3.8.0
+typepy==1.3.5
+typer==0.27.2
+typing-extensions==4.16.0
+typing-inspection==0.4.4
+urllib3==2.4.0
+wcwidth==0.2.13
+word2number==1.1
+xxhash==4.0.1