Instructions to use lemon07r/Gemma-2-Ataraxy-Advanced-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use lemon07r/Gemma-2-Ataraxy-Advanced-9B with Transformers:

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

pipe = pipeline("text-generation", model="lemon07r/Gemma-2-Ataraxy-Advanced-9B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("lemon07r/Gemma-2-Ataraxy-Advanced-9B")
model = AutoModelForCausalLM.from_pretrained("lemon07r/Gemma-2-Ataraxy-Advanced-9B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.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=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use lemon07r/Gemma-2-Ataraxy-Advanced-9B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "lemon07r/Gemma-2-Ataraxy-Advanced-9B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "lemon07r/Gemma-2-Ataraxy-Advanced-9B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/lemon07r/Gemma-2-Ataraxy-Advanced-9B

SGLang

How to use lemon07r/Gemma-2-Ataraxy-Advanced-9B 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 "lemon07r/Gemma-2-Ataraxy-Advanced-9B" \
    --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": "lemon07r/Gemma-2-Ataraxy-Advanced-9B",
		"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 "lemon07r/Gemma-2-Ataraxy-Advanced-9B" \
        --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": "lemon07r/Gemma-2-Ataraxy-Advanced-9B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use lemon07r/Gemma-2-Ataraxy-Advanced-9B with Docker Model Runner:
```
docker model run hf.co/lemon07r/Gemma-2-Ataraxy-Advanced-9B
```

Gemma-2-Ataraxy-Advanced-9B / README.md

lemon07r

Adding Evaluation Results (#1)

856bde5 verified over 1 year ago

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	---
	library_name: transformers
	tags:
	- mergekit
	- merge
	base_model:
	- jsgreenawalt/gemma-2-9B-it-advanced-v2.1
	- lemon07r/Gemma-2-Ataraxy-9B
	model-index:
	- name: Gemma-2-Ataraxy-Advanced-9B
	results:
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: IFEval (0-Shot)
	type: HuggingFaceH4/ifeval
	args:
	num_few_shot: 0
	metrics:
	- type: inst_level_strict_acc and prompt_level_strict_acc
	value: 55.16
	name: strict accuracy
	source:
	url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-Advanced-9B
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: BBH (3-Shot)
	type: BBH
	args:
	num_few_shot: 3
	metrics:
	- type: acc_norm
	value: 41.16
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-Advanced-9B
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: MATH Lvl 5 (4-Shot)
	type: hendrycks/competition_math
	args:
	num_few_shot: 4
	metrics:
	- type: exact_match
	value: 0.15
	name: exact match
	source:
	url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-Advanced-9B
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: GPQA (0-shot)
	type: Idavidrein/gpqa
	args:
	num_few_shot: 0
	metrics:
	- type: acc_norm
	value: 11.41
	name: acc_norm
	source:
	url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-Advanced-9B
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: MuSR (0-shot)
	type: TAUR-Lab/MuSR
	args:
	num_few_shot: 0
	metrics:
	- type: acc_norm
	value: 6.51
	name: acc_norm
	source:
	url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-Advanced-9B
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: MMLU-PRO (5-shot)
	type: TIGER-Lab/MMLU-Pro
	config: main
	split: test
	args:
	num_few_shot: 5
	metrics:
	- type: acc
	value: 36.04
	name: accuracy
	source:
	url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=lemon07r/Gemma-2-Ataraxy-Advanced-9B
	name: Open LLM Leaderboard
	---
	# Gemma-2-Ataraxy-Advanced-9B

	Another test model that you should probably ignore.

	This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

	## Merge Details
	### Merge Method

	This model was merged using the SLERP merge method.

	### Models Merged

	The following models were included in the merge:
	* [jsgreenawalt/gemma-2-9B-it-advanced-v2.1](https://huggingface.co/jsgreenawalt/gemma-2-9B-it-advanced-v2.1)
	* [lemon07r/Gemma-2-Ataraxy-9B](https://huggingface.co/lemon07r/Gemma-2-Ataraxy-9B)

	### Configuration

	The following YAML configuration was used to produce this model:

	```yaml
	base_model: jsgreenawalt/gemma-2-9B-it-advanced-v2.1
	dtype: bfloat16
	merge_method: slerp
	parameters:
	t:
	- filter: self_attn
	value: [0.0, 0.5, 0.3, 0.7, 1.0]
	- filter: mlp
	value: [1.0, 0.5, 0.7, 0.3, 0.0]
	- value: 0.5
	slices:
	- sources:
	- layer_range: [0, 42]
	model: lemon07r/Gemma-2-Ataraxy-9B
	- layer_range: [0, 42]
	model: jsgreenawalt/gemma-2-9B-it-advanced-v2.1
	```

	# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
	Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_lemon07r__Gemma-2-Ataraxy-Advanced-9B)

	\| Metric \|Value\|
	\|-------------------\|----:\|
	\|Avg. \|25.07\|
	\|IFEval (0-Shot) \|55.16\|
	\|BBH (3-Shot) \|41.16\|
	\|MATH Lvl 5 (4-Shot)\| 0.15\|
	\|GPQA (0-shot) \|11.41\|
	\|MuSR (0-shot) \| 6.51\|
	\|MMLU-PRO (5-shot) \|36.04\|