Instructions to use Gille/StrangeMerges_52-7B-dare_ties with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Gille/StrangeMerges_52-7B-dare_ties with Transformers:

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

pipe = pipeline("text-generation", model="Gille/StrangeMerges_52-7B-dare_ties")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Gille/StrangeMerges_52-7B-dare_ties")
model = AutoModelForCausalLM.from_pretrained("Gille/StrangeMerges_52-7B-dare_ties", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Gille/StrangeMerges_52-7B-dare_ties with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Gille/StrangeMerges_52-7B-dare_ties"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Gille/StrangeMerges_52-7B-dare_ties",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Gille/StrangeMerges_52-7B-dare_ties

SGLang

How to use Gille/StrangeMerges_52-7B-dare_ties 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 "Gille/StrangeMerges_52-7B-dare_ties" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Gille/StrangeMerges_52-7B-dare_ties",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "Gille/StrangeMerges_52-7B-dare_ties" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Gille/StrangeMerges_52-7B-dare_ties",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Gille/StrangeMerges_52-7B-dare_ties with Docker Model Runner:
```
docker model run hf.co/Gille/StrangeMerges_52-7B-dare_ties
```

StrangeMerges_52-7B-dare_ties / README.md

Gille

leaderboard-pr-bot

Adding Evaluation Results (#1)

0196ec7 verified over 2 years ago

preview code

Raw History Blame Contribute Delete

5.79 kB

---
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- WizardLM/WizardMath-7B-V1.1
- AurelPx/Percival_01-7b-slerp
- Weyaxi/Einstein-v4-7B
- Kukedlc/NeuralMaths-Experiment-7b
- Gille/StrangeMerges_35-7B-slerp
base_model:
- WizardLM/WizardMath-7B-V1.1
- AurelPx/Percival_01-7b-slerp
- Weyaxi/Einstein-v4-7B
- Kukedlc/NeuralMaths-Experiment-7b
- Gille/StrangeMerges_35-7B-slerp
model-index:
- name: StrangeMerges_52-7B-dare_ties
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: AI2 Reasoning Challenge (25-Shot)
      type: ai2_arc
      config: ARC-Challenge
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: acc_norm
      value: 69.03
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_52-7B-dare_ties
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HellaSwag (10-Shot)
      type: hellaswag
      split: validation
      args:
        num_few_shot: 10
    metrics:
    - type: acc_norm
      value: 87.15
      name: normalized accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_52-7B-dare_ties
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU (5-Shot)
      type: cais/mmlu
      config: all
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 64.94
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_52-7B-dare_ties
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: TruthfulQA (0-shot)
      type: truthful_qa
      config: multiple_choice
      split: validation
      args:
        num_few_shot: 0
    metrics:
    - type: mc2
      value: 65.76
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_52-7B-dare_ties
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Winogrande (5-shot)
      type: winogrande
      config: winogrande_xl
      split: validation
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 81.93
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_52-7B-dare_ties
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GSM8k (5-shot)
      type: gsm8k
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 72.25
      name: accuracy
    source:
      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_52-7B-dare_ties
      name: Open LLM Leaderboard
---
# StrangeMerges_52-7B-dare_ties

StrangeMerges_52-7B-dare_ties is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [WizardLM/WizardMath-7B-V1.1](https://huggingface.co/WizardLM/WizardMath-7B-V1.1)
* [AurelPx/Percival_01-7b-slerp](https://huggingface.co/AurelPx/Percival_01-7b-slerp)
* [Weyaxi/Einstein-v4-7B](https://huggingface.co/Weyaxi/Einstein-v4-7B)
* [Kukedlc/NeuralMaths-Experiment-7b](https://huggingface.co/Kukedlc/NeuralMaths-Experiment-7b)
* [Gille/StrangeMerges_35-7B-slerp](https://huggingface.co/Gille/StrangeMerges_35-7B-slerp)

## 🧩 Configuration

```yaml
models:
  - model: Gille/StrangeMerges_51-7B-dare_ties
    # No parameters necessary for base model
  - model: WizardLM/WizardMath-7B-V1.1
    parameters:
      density: 0.66
      weight: 0.2
  - model: AurelPx/Percival_01-7b-slerp
    parameters:
      density: 0.55
      weight: 0.2
  - model: Weyaxi/Einstein-v4-7B
    parameters:
      density: 0.55
      weight: 0.2
  - model: Kukedlc/NeuralMaths-Experiment-7b
    parameters:
      density: 0.44
      weight: 0.2
  - model: Gille/StrangeMerges_35-7B-slerp
    parameters:
      density: 0.66
      weight: 0.2
merge_method: dare_ties
base_model: Gille/StrangeMerges_51-7B-dare_ties
parameters:
  int8_mask: true
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Gille/StrangeMerges_52-7B-dare_ties"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Gille__StrangeMerges_52-7B-dare_ties)

|             Metric              |Value|
|---------------------------------|----:|
|Avg.                             |73.51|
|AI2 Reasoning Challenge (25-Shot)|69.03|
|HellaSwag (10-Shot)              |87.15|
|MMLU (5-Shot)                    |64.94|
|TruthfulQA (0-shot)              |65.76|
|Winogrande (5-shot)              |81.93|
|GSM8k (5-shot)                   |72.25|

	---
	license: apache-2.0
	tags:
	- merge
	- mergekit
	- lazymergekit
	- WizardLM/WizardMath-7B-V1.1
	- AurelPx/Percival_01-7b-slerp
	- Weyaxi/Einstein-v4-7B
	- Kukedlc/NeuralMaths-Experiment-7b
	- Gille/StrangeMerges_35-7B-slerp
	base_model:
	- WizardLM/WizardMath-7B-V1.1
	- AurelPx/Percival_01-7b-slerp
	- Weyaxi/Einstein-v4-7B
	- Kukedlc/NeuralMaths-Experiment-7b
	- Gille/StrangeMerges_35-7B-slerp
	model-index:
	- name: StrangeMerges_52-7B-dare_ties
	results:
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: AI2 Reasoning Challenge (25-Shot)
	type: ai2_arc
	config: ARC-Challenge
	split: test
	args:
	num_few_shot: 25
	metrics:
	- type: acc_norm
	value: 69.03
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_52-7B-dare_ties
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: HellaSwag (10-Shot)
	type: hellaswag
	split: validation
	args:
	num_few_shot: 10
	metrics:
	- type: acc_norm
	value: 87.15
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_52-7B-dare_ties
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: MMLU (5-Shot)
	type: cais/mmlu
	config: all
	split: test
	args:
	num_few_shot: 5
	metrics:
	- type: acc
	value: 64.94
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_52-7B-dare_ties
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: TruthfulQA (0-shot)
	type: truthful_qa
	config: multiple_choice
	split: validation
	args:
	num_few_shot: 0
	metrics:
	- type: mc2
	value: 65.76
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_52-7B-dare_ties
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: Winogrande (5-shot)
	type: winogrande
	config: winogrande_xl
	split: validation
	args:
	num_few_shot: 5
	metrics:
	- type: acc
	value: 81.93
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_52-7B-dare_ties
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: GSM8k (5-shot)
	type: gsm8k
	config: main
	split: test
	args:
	num_few_shot: 5
	metrics:
	- type: acc
	value: 72.25
	name: accuracy
	source:
	url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Gille/StrangeMerges_52-7B-dare_ties
	name: Open LLM Leaderboard
	---

	# StrangeMerges_52-7B-dare_ties

	StrangeMerges_52-7B-dare_ties is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
	* [WizardLM/WizardMath-7B-V1.1](https://huggingface.co/WizardLM/WizardMath-7B-V1.1)
	* [AurelPx/Percival_01-7b-slerp](https://huggingface.co/AurelPx/Percival_01-7b-slerp)
	* [Weyaxi/Einstein-v4-7B](https://huggingface.co/Weyaxi/Einstein-v4-7B)
	* [Kukedlc/NeuralMaths-Experiment-7b](https://huggingface.co/Kukedlc/NeuralMaths-Experiment-7b)
	* [Gille/StrangeMerges_35-7B-slerp](https://huggingface.co/Gille/StrangeMerges_35-7B-slerp)

	## 🧩 Configuration

	```yaml
	models:
	- model: Gille/StrangeMerges_51-7B-dare_ties
	# No parameters necessary for base model
	- model: WizardLM/WizardMath-7B-V1.1
	parameters:
	density: 0.66
	weight: 0.2
	- model: AurelPx/Percival_01-7b-slerp
	parameters:
	density: 0.55
	weight: 0.2
	- model: Weyaxi/Einstein-v4-7B
	parameters:
	density: 0.55
	weight: 0.2
	- model: Kukedlc/NeuralMaths-Experiment-7b
	parameters:
	density: 0.44
	weight: 0.2
	- model: Gille/StrangeMerges_35-7B-slerp
	parameters:
	density: 0.66
	weight: 0.2
	merge_method: dare_ties
	base_model: Gille/StrangeMerges_51-7B-dare_ties
	parameters:
	int8_mask: true
	dtype: bfloat16
	```

	## 💻 Usage

	```python
	!pip install -qU transformers accelerate

	from transformers import AutoTokenizer
	import transformers
	import torch

	model = "Gille/StrangeMerges_52-7B-dare_ties"
	messages = [{"role": "user", "content": "What is a large language model?"}]

	tokenizer = AutoTokenizer.from_pretrained(model)
	prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
	pipeline = transformers.pipeline(
	"text-generation",
	model=model,
	torch_dtype=torch.float16,
	device_map="auto",
	)

	outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
	print(outputs[0]["generated_text"])
	```
	# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
	Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Gille__StrangeMerges_52-7B-dare_ties)

	\| Metric \|Value\|
	\|---------------------------------\|----:\|
	\|Avg. \|73.51\|
	\|AI2 Reasoning Challenge (25-Shot)\|69.03\|
	\|HellaSwag (10-Shot) \|87.15\|
	\|MMLU (5-Shot) \|64.94\|
	\|TruthfulQA (0-shot) \|65.76\|
	\|Winogrande (5-shot) \|81.93\|
	\|GSM8k (5-shot) \|72.25\|