Instructions to use TableCheck/gemma-3-27b-it-ft-query-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TableCheck/gemma-3-27b-it-ft-query-extraction with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-3-27b-it-unsloth-bnb-4bit")
model = PeftModel.from_pretrained(base_model, "TableCheck/gemma-3-27b-it-ft-query-extraction")

Transformers

How to use TableCheck/gemma-3-27b-it-ft-query-extraction with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("TableCheck/gemma-3-27b-it-ft-query-extraction", dtype="auto")

llama-cpp-python

How to use TableCheck/gemma-3-27b-it-ft-query-extraction with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="TableCheck/gemma-3-27b-it-ft-query-extraction",
	filename="abc.BF16-00001-of-00002.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use TableCheck/gemma-3-27b-it-ft-query-extraction with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf TableCheck/gemma-3-27b-it-ft-query-extraction:BF16
# Run inference directly in the terminal:
llama-cli -hf TableCheck/gemma-3-27b-it-ft-query-extraction:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf TableCheck/gemma-3-27b-it-ft-query-extraction:BF16
# Run inference directly in the terminal:
llama-cli -hf TableCheck/gemma-3-27b-it-ft-query-extraction:BF16

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 TableCheck/gemma-3-27b-it-ft-query-extraction:BF16
# Run inference directly in the terminal:
./llama-cli -hf TableCheck/gemma-3-27b-it-ft-query-extraction:BF16

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 TableCheck/gemma-3-27b-it-ft-query-extraction:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf TableCheck/gemma-3-27b-it-ft-query-extraction:BF16

Use Docker

docker model run hf.co/TableCheck/gemma-3-27b-it-ft-query-extraction:BF16

LM Studio
Jan
Ollama
How to use TableCheck/gemma-3-27b-it-ft-query-extraction with Ollama:
```
ollama run hf.co/TableCheck/gemma-3-27b-it-ft-query-extraction:BF16
```

Unsloth Studio

How to use TableCheck/gemma-3-27b-it-ft-query-extraction 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 TableCheck/gemma-3-27b-it-ft-query-extraction 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 TableCheck/gemma-3-27b-it-ft-query-extraction to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for TableCheck/gemma-3-27b-it-ft-query-extraction to start chatting

Atomic Chat new
Docker Model Runner
How to use TableCheck/gemma-3-27b-it-ft-query-extraction with Docker Model Runner:
```
docker model run hf.co/TableCheck/gemma-3-27b-it-ft-query-extraction:BF16
```

Lemonade

How to use TableCheck/gemma-3-27b-it-ft-query-extraction with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull TableCheck/gemma-3-27b-it-ft-query-extraction:BF16

Run and chat with the model

lemonade run user.gemma-3-27b-it-ft-query-extraction-BF16

List all available models

lemonade list

gemma-3-27b-it-ft-query-extraction

File size: 868 Bytes

1f02ac9

{
  "alpha_pattern": {},
  "auto_mapping": null,
  "base_model_name_or_path": "unsloth/gemma-3-27b-it-unsloth-bnb-4bit",
  "bias": "none",
  "corda_config": null,
  "eva_config": null,
  "exclude_modules": null,
  "fan_in_fan_out": false,
  "inference_mode": true,
  "init_lora_weights": true,
  "layer_replication": null,
  "layers_pattern": null,
  "layers_to_transform": null,
  "loftq_config": {},
  "lora_alpha": 16,
  "lora_bias": false,
  "lora_dropout": 0,
  "megatron_config": null,
  "megatron_core": "megatron.core",
  "modules_to_save": null,
  "peft_type": "LORA",
  "r": 8,
  "rank_pattern": {},
  "revision": null,
  "target_modules": [
    "k_proj",
    "down_proj",
    "up_proj",
    "o_proj",
    "v_proj",
    "q_proj",
    "gate_proj"
  ],
  "task_type": "CAUSAL_LM",
  "trainable_token_indices": null,
  "use_dora": false,
  "use_rslora": false
}