Instructions to use DreadPoor/Spring_Dusk-8B-SCE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DreadPoor/Spring_Dusk-8B-SCE with Transformers:

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

pipe = pipeline("text-generation", model="DreadPoor/Spring_Dusk-8B-SCE")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("DreadPoor/Spring_Dusk-8B-SCE")
model = AutoModelForCausalLM.from_pretrained("DreadPoor/Spring_Dusk-8B-SCE")
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

vLLM

How to use DreadPoor/Spring_Dusk-8B-SCE with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DreadPoor/Spring_Dusk-8B-SCE"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DreadPoor/Spring_Dusk-8B-SCE",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/DreadPoor/Spring_Dusk-8B-SCE

SGLang

How to use DreadPoor/Spring_Dusk-8B-SCE 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 "DreadPoor/Spring_Dusk-8B-SCE" \
    --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": "DreadPoor/Spring_Dusk-8B-SCE",
		"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 "DreadPoor/Spring_Dusk-8B-SCE" \
        --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": "DreadPoor/Spring_Dusk-8B-SCE",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use DreadPoor/Spring_Dusk-8B-SCE with Docker Model Runner:
```
docker model run hf.co/DreadPoor/Spring_Dusk-8B-SCE
```

Spring_Dusk-8B-SCE / README.md

DreadPoor

Adding Evaluation Results (#1)

def8ef0 verified over 1 year ago

preview code

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	---
	base_model:
	- johnsutor/Llama-3-8B-Instruct_dare_ties-density-0.9
	- FuseAI/FuseChat-Llama-3.1-8B-SFT
	- refuelai/Llama-3-Refueled
	- DreadPoor/Derivative-8B-Model_Stock
	- Joseph717171/Llama-3.1-SuperNova-8B-Lite_TIES_with_Base
	library_name: transformers
	tags:
	- mergekit
	- merge
	model-index:
	- name: Spring_Dusk-8B-SCE
	results:
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: IFEval (0-Shot)
	type: wis-k/instruction-following-eval
	split: train
	args:
	num_few_shot: 0
	metrics:
	- type: inst_level_strict_acc and prompt_level_strict_acc
	value: 65.15
	name: averaged accuracy
	source:
	url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=DreadPoor%2FSpring_Dusk-8B-SCE
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: BBH (3-Shot)
	type: SaylorTwift/bbh
	split: test
	args:
	num_few_shot: 3
	metrics:
	- type: acc_norm
	value: 37.76
	name: normalized accuracy
	source:
	url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=DreadPoor%2FSpring_Dusk-8B-SCE
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: MATH Lvl 5 (4-Shot)
	type: lighteval/MATH-Hard
	split: test
	args:
	num_few_shot: 4
	metrics:
	- type: exact_match
	value: 7.4
	name: exact match
	source:
	url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=DreadPoor%2FSpring_Dusk-8B-SCE
	name: Open LLM Leaderboard
	- task:
	type: text-generation
	name: Text Generation
	dataset:
	name: GPQA (0-shot)
	type: Idavidrein/gpqa
	split: train
	args:
	num_few_shot: 0
	metrics:
	- type: acc_norm
	value: 5.03
	name: acc_norm
	source:
	url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=DreadPoor%2FSpring_Dusk-8B-SCE
	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: 17.33
	name: acc_norm
	source:
	url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=DreadPoor%2FSpring_Dusk-8B-SCE
	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: 27.06
	name: accuracy
	source:
	url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=DreadPoor%2FSpring_Dusk-8B-SCE
	name: Open LLM Leaderboard
	---
	# merge

	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 [SCE](https://arxiv.org/abs/2408.07990) merge method using [FuseAI/FuseChat-Llama-3.1-8B-SFT](https://huggingface.co/FuseAI/FuseChat-Llama-3.1-8B-SFT) as a base.

	### Models Merged

	The following models were included in the merge:
	* [johnsutor/Llama-3-8B-Instruct_dare_ties-density-0.9](https://huggingface.co/johnsutor/Llama-3-8B-Instruct_dare_ties-density-0.9)
	* [refuelai/Llama-3-Refueled](https://huggingface.co/refuelai/Llama-3-Refueled)
	* [DreadPoor/Derivative-8B-Model_Stock](https://huggingface.co/DreadPoor/Derivative-8B-Model_Stock)
	* [Joseph717171/Llama-3.1-SuperNova-8B-Lite_TIES_with_Base](https://huggingface.co/Joseph717171/Llama-3.1-SuperNova-8B-Lite_TIES_with_Base)

	### Configuration

	The following YAML configuration was used to produce this model:

	```yaml
	models:
	- model: refuelai/Llama-3-Refueled
	- model: johnsutor/Llama-3-8B-Instruct_dare_ties-density-0.9
	- model: Joseph717171/Llama-3.1-SuperNova-8B-Lite_TIES_with_Base
	- model: DreadPoor/Derivative-8B-Model_Stock
	merge_method: sce
	base_model: FuseAI/FuseChat-Llama-3.1-8B-SFT
	parameters:
	select_topk: 0.3
	dtype: bfloat16
	```

	# [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/DreadPoor__Spring_Dusk-8B-SCE-details)!
	Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=DreadPoor%2FSpring_Dusk-8B-SCE&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!

	\| Metric \|Value (%)\|
	\|-------------------\|--------:\|
	\|Average \| 26.62\|
	\|IFEval (0-Shot) \| 65.15\|
	\|BBH (3-Shot) \| 37.76\|
	\|MATH Lvl 5 (4-Shot)\| 7.40\|
	\|GPQA (0-shot) \| 5.03\|
	\|MuSR (0-shot) \| 17.33\|
	\|MMLU-PRO (5-shot) \| 27.06\|