Instructions to use paul-stansifer/qw3-gemma2-9b-1x6e-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use paul-stansifer/qw3-gemma2-9b-1x6e-4 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 paul-stansifer/qw3-gemma2-9b-1x6e-4:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf paul-stansifer/qw3-gemma2-9b-1x6e-4:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf paul-stansifer/qw3-gemma2-9b-1x6e-4:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf paul-stansifer/qw3-gemma2-9b-1x6e-4: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 paul-stansifer/qw3-gemma2-9b-1x6e-4:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf paul-stansifer/qw3-gemma2-9b-1x6e-4: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 paul-stansifer/qw3-gemma2-9b-1x6e-4:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf paul-stansifer/qw3-gemma2-9b-1x6e-4:Q4_K_M

Use Docker

docker model run hf.co/paul-stansifer/qw3-gemma2-9b-1x6e-4:Q4_K_M

LM Studio
Jan

vLLM

How to use paul-stansifer/qw3-gemma2-9b-1x6e-4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "paul-stansifer/qw3-gemma2-9b-1x6e-4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "paul-stansifer/qw3-gemma2-9b-1x6e-4",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/paul-stansifer/qw3-gemma2-9b-1x6e-4:Q4_K_M

Ollama
How to use paul-stansifer/qw3-gemma2-9b-1x6e-4 with Ollama:
```
ollama run hf.co/paul-stansifer/qw3-gemma2-9b-1x6e-4:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use paul-stansifer/qw3-gemma2-9b-1x6e-4 with Docker Model Runner:
```
docker model run hf.co/paul-stansifer/qw3-gemma2-9b-1x6e-4:Q4_K_M
```

Lemonade

How to use paul-stansifer/qw3-gemma2-9b-1x6e-4 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull paul-stansifer/qw3-gemma2-9b-1x6e-4:Q4_K_M

Run and chat with the model

lemonade run user.qw3-gemma2-9b-1x6e-4-Q4_K_M

List all available models

lemonade list

Atomic Chat

paul-stansifer commited on Feb 16

Commit

dc6d1ed

verified ·

1 Parent(s): 2798126

Upload model trained with Unsloth

Browse files

Upload model trained with Unsloth 2x faster

Files changed (2) hide show

adapter_config.json +50 -0
adapter_model.safetensors +3 -0

adapter_config.json ADDED Viewed

	@@ -0,0 +1,50 @@

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+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "Gemma2ForCausalLM",
+    "parent_library": "transformers.models.gemma2.modeling_gemma2",
+    "unsloth_fixed": true
+  },
+  "base_model_name_or_path": "unsloth/gemma-2-9b-bnb-4bit",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
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+  "inference_mode": true,
+  "init_lora_weights": true,
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+  "lora_bias": false,
+  "lora_dropout": 0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.1",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "up_proj",
+    "gate_proj",
+    "k_proj",
+    "o_proj",
+    "down_proj",
+    "v_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

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