Image-Text-to-Text
PEFT
Safetensors
GGUF
microscopy
vision-language
diatoms
fungal-spores
biology
bioindicator
gemma-4
unsloth
qlora
multimodal
on-device
offline
conversational
Instructions to use Laborator/microlens-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Laborator/microlens-final with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-4-e2b-it-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "Laborator/microlens-final") - llama-cpp-python
How to use Laborator/microlens-final with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Laborator/microlens-final", filename="mmproj.gguf", )
llm.create_chat_completion( 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" } } ] } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Laborator/microlens-final 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 Laborator/microlens-final # Run inference directly in the terminal: llama cli -hf Laborator/microlens-final
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Laborator/microlens-final # Run inference directly in the terminal: llama cli -hf Laborator/microlens-final
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 Laborator/microlens-final # Run inference directly in the terminal: ./llama-cli -hf Laborator/microlens-final
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 Laborator/microlens-final # Run inference directly in the terminal: ./build/bin/llama-cli -hf Laborator/microlens-final
Use Docker
docker model run hf.co/Laborator/microlens-final
- LM Studio
- Jan
- vLLM
How to use Laborator/microlens-final with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Laborator/microlens-final" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Laborator/microlens-final", "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/Laborator/microlens-final
- Ollama
How to use Laborator/microlens-final with Ollama:
ollama run hf.co/Laborator/microlens-final
- Unsloth Studio
How to use Laborator/microlens-final 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 Laborator/microlens-final 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 Laborator/microlens-final to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Laborator/microlens-final to start chatting
- Pi
How to use Laborator/microlens-final with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Laborator/microlens-final
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "Laborator/microlens-final" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Laborator/microlens-final with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Laborator/microlens-final
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 Laborator/microlens-final
Run Hermes
hermes
- Atomic Chat new
- OpenClaw new
How to use Laborator/microlens-final with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Laborator/microlens-final
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 "Laborator/microlens-final" \ --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"
- Docker Model Runner
How to use Laborator/microlens-final with Docker Model Runner:
docker model run hf.co/Laborator/microlens-final
- Lemonade
How to use Laborator/microlens-final with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Laborator/microlens-final
Run and chat with the model
lemonade run user.microlens-final-{{QUANT_TAG}}List all available models
lemonade list
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| "alora_invocation_tokens": null, | |
| "alpha_pattern": {}, | |
| "arrow_config": null, | |
| "auto_mapping": { | |
| "base_model_class": "Gemma4ForConditionalGeneration", | |
| "parent_library": "transformers.models.gemma4.modeling_gemma4", | |
| "unsloth_fixed": true | |
| }, | |
| "base_model_name_or_path": "unsloth/gemma-4-e2b-it-unsloth-bnb-4bit", | |
| "bias": "none", | |
| "corda_config": null, | |
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| "layers_to_transform": null, | |
| "loftq_config": {}, | |
| "lora_alpha": 32, | |
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| "megatron_config": null, | |
| "megatron_core": "megatron.core", | |
| "modules_to_save": null, | |
| "peft_type": "LORA", | |
| "peft_version": "0.18.0", | |
| "qalora_group_size": 16, | |
| "r": 16, | |
| "rank_pattern": {}, | |
| "revision": null, | |
| "target_modules": "(?:.*?(?:vision|image|visual|patch|language|text).*?(?:self_attn|attention|attn|mlp|feed_forward|ffn|dense).*?(?:k_proj|q_proj|v_proj|o_proj|gate_proj|up_proj|down_proj|per_layer_input_gate|per_layer_projection|linear|embedding_projection|relative_k_proj).*?)|(?:\\bmodel\\.layers\\.[\\d]{1,}\\.(?:self_attn|attention|attn|mlp|feed_forward|ffn|dense)\\.(?:(?:k_proj|q_proj|v_proj|o_proj|gate_proj|up_proj|down_proj|per_layer_input_gate|per_layer_projection|linear|embedding_projection|relative_k_proj)))", | |
| "target_parameters": null, | |
| "task_type": "CAUSAL_LM", | |
| "trainable_token_indices": null, | |
| "use_dora": false, | |
| "use_qalora": false, | |
| "use_rslora": false | |
| } |