Instructions to use MaziyarPanahi/gemma-2b-it-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use MaziyarPanahi/gemma-2b-it-GGUF with Transformers:

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

pipe = pipeline("text-generation", model="MaziyarPanahi/gemma-2b-it-GGUF")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("MaziyarPanahi/gemma-2b-it-GGUF", dtype="auto")

llama-cpp-python

How to use MaziyarPanahi/gemma-2b-it-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="MaziyarPanahi/gemma-2b-it-GGUF",
	filename="gemma-2b-it.Q2_K.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use MaziyarPanahi/gemma-2b-it-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf MaziyarPanahi/gemma-2b-it-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf MaziyarPanahi/gemma-2b-it-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf MaziyarPanahi/gemma-2b-it-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf MaziyarPanahi/gemma-2b-it-GGUF:Q4_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 MaziyarPanahi/gemma-2b-it-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf MaziyarPanahi/gemma-2b-it-GGUF:Q4_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 MaziyarPanahi/gemma-2b-it-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf MaziyarPanahi/gemma-2b-it-GGUF:Q4_K_M

Use Docker

docker model run hf.co/MaziyarPanahi/gemma-2b-it-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use MaziyarPanahi/gemma-2b-it-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "MaziyarPanahi/gemma-2b-it-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "MaziyarPanahi/gemma-2b-it-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/MaziyarPanahi/gemma-2b-it-GGUF:Q4_K_M

SGLang

How to use MaziyarPanahi/gemma-2b-it-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 "MaziyarPanahi/gemma-2b-it-GGUF" \
    --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": "MaziyarPanahi/gemma-2b-it-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "MaziyarPanahi/gemma-2b-it-GGUF" \
        --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": "MaziyarPanahi/gemma-2b-it-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use MaziyarPanahi/gemma-2b-it-GGUF with Ollama:
```
ollama run hf.co/MaziyarPanahi/gemma-2b-it-GGUF:Q4_K_M
```

Unsloth Studio

How to use MaziyarPanahi/gemma-2b-it-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 MaziyarPanahi/gemma-2b-it-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 MaziyarPanahi/gemma-2b-it-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for MaziyarPanahi/gemma-2b-it-GGUF to start chatting

Docker Model Runner
How to use MaziyarPanahi/gemma-2b-it-GGUF with Docker Model Runner:
```
docker model run hf.co/MaziyarPanahi/gemma-2b-it-GGUF:Q4_K_M
```

Lemonade

How to use MaziyarPanahi/gemma-2b-it-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull MaziyarPanahi/gemma-2b-it-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.gemma-2b-it-GGUF-Q4_K_M

List all available models

lemonade list

Error in recognizing the file gemma-2b-it.Q8_0.gguf, updated llmam cpp and made new binaries

by auralodyssey - opened Feb 21, 2024

Discussion

auralodyssey

Feb 21, 2024

Im facing the following error

ggml_init_cublas: CUDA_USE_TENSOR_CORES: yes
ggml_init_cublas: found 1 CUDA devices:
Device 0: NVIDIA GeForce RTX 3070 Laptop GPU, compute capability 8.6, VMM: yes
llama_model_loader: loaded meta data with 21 key-value pairs and 164 tensors from E:\LLM\Mixtral\gemma-2b-it.q8_0.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = gemma
llama_model_loader: - kv 1: general.name str = gemma-2b-it
llama_model_loader: - kv 2: gemma.context_length u32 = 8192
llama_model_loader: - kv 3: gemma.block_count u32 = 18
llama_model_loader: - kv 4: gemma.embedding_length u32 = 2048
llama_model_loader: - kv 5: gemma.feed_forward_length u32 = 16384
llama_model_loader: - kv 6: gemma.attention.head_count u32 = 8
llama_model_loader: - kv 7: gemma.attention.head_count_kv u32 = 1
llama_model_loader: - kv 8: gemma.attention.key_length u32 = 256
llama_model_loader: - kv 9: gemma.attention.value_length u32 = 256
llama_model_loader: - kv 10: gemma.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 11: tokenizer.ggml.model str = llama
llama_model_loader: - kv 12: tokenizer.ggml.bos_token_id u32 = 2
llama_model_loader: - kv 13: tokenizer.ggml.eos_token_id u32 = 1
llama_model_loader: - kv 14: tokenizer.ggml.padding_token_id u32 = 0
llama_model_loader: - kv 15: tokenizer.ggml.unknown_token_id u32 = 3
llama_model_loader: - kv 16: tokenizer.ggml.tokens arr[str,256128] = ["", "", "", "", ...
llama_model_loader: - kv 17: tokenizer.ggml.scores arr[f32,256128] = [0.000000, 0.000000, 0.000000, 0.0000...
llama_model_loader: - kv 18: tokenizer.ggml.token_type arr[i32,256128] = [3, 3, 3, 2, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 19: general.quantization_version u32 = 2
llama_model_loader: - kv 20: general.file_type u32 = 7
llama_model_loader: - type f32: 37 tensors
llama_model_loader: - type q8_0: 127 tensors
error loading model: unknown model architecture: 'gemma'
llama_load_model_from_file: failed to load model
AVX = 1 | AVX_VNNI = 0 | AVX2 = 1 | AVX512 = 0 | AVX512_VBMI = 0 | AVX512_VNNI = 0 | FMA = 1 | NEON = 0 | ARM_FMA = 0 | F16C = 1 | FP16_VA = 0 | WASM_SIMD = 0 | BLAS = 1 | SSE3 = 1 | SSSE3 = 0 | VSX = 0 |
Traceback (most recent call last):
File "e:\LLM\Mixtral\Priyansh\llm_processing.py", line 12, in
llm = Llama(model_path=model_path, n_ctx=4096, n_threads=11, n_gpu_layers=8) #changed model loading method for gemma
File "E:\LLM\Mixtral\mixtral_llm\lib\site-packages\llama_cpp\llama.py", line 962, in init
self._n_vocab = self.n_vocab()
File "E:\LLM\Mixtral\mixtral_llm\lib\site-packages\llama_cpp\llama.py", line 2274, in n_vocab
return self._model.n_vocab()
File "E:\LLM\Mixtral\mixtral_llm\lib\site-packages\llama_cpp\llama.py", line 251, in n_vocab
assert self.model is not None
AssertionError

Any ideas why?

MaziyarPanahi

Owner Feb 21, 2024

@auralodyssey it seems there is an issue with both converting Gemma to GGUF, and using the original GGUF by Google to quantize models: https://github.com/ggerganov/llama.cpp/issues/5635

However, this error is different. If you pull the latest changes from the main in llama.cpp and re-build it again you shouldn't see this error. (at least I won't, it's just the quality that is a bit strange for the moment)

auralodyssey

Feb 21, 2024

•

edited Feb 21, 2024

@auralodyssey it seems there is an issue with both converting Gemma to GGUF, and using the original GGUF by Google to quantize models: https://github.com/ggerganov/llama.cpp/issues/5635

However, this error is different. If you pull the latest changes from the main in llama.cpp and re-build it again you shouldn't see this error. (at least I won't, it's just the quality that is a bit strange for the moment)

I have done the updating and rebuilding. I had cloned using git pull and then remade the build folder but still the error is occurring. Am i missing something? Even LM Studio is showing unsupported architecture.

MaziyarPanahi

Owner Feb 21, 2024

@auralodyssey all I can say for now only the original GGUF model provided by Google works, any other convert or quantization don't work. I think we have to wait for some newer changes in llama.cpp and followup in the issue I shared to confirm everything works

MaziyarPanahi

Owner Feb 27, 2024

This should be fine now with good responses

MaziyarPanahi changed discussion status to closed Feb 27, 2024

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment