Instructions to use mrfakename/NeuralOrca-7B-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mrfakename/NeuralOrca-7B-v1 with Transformers:

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

pipe = pipeline("text-generation", model="mrfakename/NeuralOrca-7B-v1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("mrfakename/NeuralOrca-7B-v1")
model = AutoModelForMultimodalLM.from_pretrained("mrfakename/NeuralOrca-7B-v1")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use mrfakename/NeuralOrca-7B-v1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "mrfakename/NeuralOrca-7B-v1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "mrfakename/NeuralOrca-7B-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/mrfakename/NeuralOrca-7B-v1

SGLang

How to use mrfakename/NeuralOrca-7B-v1 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 "mrfakename/NeuralOrca-7B-v1" \
    --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": "mrfakename/NeuralOrca-7B-v1",
		"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 "mrfakename/NeuralOrca-7B-v1" \
        --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": "mrfakename/NeuralOrca-7B-v1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use mrfakename/NeuralOrca-7B-v1 with Docker Model Runner:
```
docker model run hf.co/mrfakename/NeuralOrca-7B-v1
```

NeuralOrca-7B-v1 / README.md

mrfakename

Adding Evaluation Results (#3)

9a826dc verified over 2 years ago

preview code

raw

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metadata

license: apache-2.0
tags:
  - merge
model-index:
  - name: NeuralOrca-7B-v1
    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: 65.27
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mrfakename/NeuralOrca-7B-v1
          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: 85.07
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mrfakename/NeuralOrca-7B-v1
          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: 63.68
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mrfakename/NeuralOrca-7B-v1
          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: 54.58
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mrfakename/NeuralOrca-7B-v1
          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: 78.77
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mrfakename/NeuralOrca-7B-v1
          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: 58.45
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mrfakename/NeuralOrca-7B-v1
          name: Open LLM Leaderboard

WARNING! This is a "Frankenmerge" - this model is untested!

NeuralOrca 7B V1

GGUF Models

By mrfakename

Please note that this is an experimental model. We cannot guarantee model quality.

This is the first (alpha) release of NeuralOrca. NeuralOrca is a merge of the following models:

mlabonne/NeuralHermes-2.5-Mistral-7B (This model is actually OpenHermes 2.5 finetuned on Intel's Neural Chat dataset and uses the ChatML prompt format, weight: 1.0)
Open-Orca/Mistral-7B-OpenOrca (This model uses the ChatML prompt format, weight: 0.7)

Prompt Format

We use the ChatML prompt format.

Example:

<|im_start|>system
You are NeuralOrca, a helpful AI assistant.
<|im_end|>
<|im_start|>user
How are you?<|im_end|>
<|im_start|>assistant

Evaluations

Coming soon

Context Length

The context length for this model is 8192 tokens (8K).

License

You are responsible for your use of NeuralOrca.

This software is licensed under the Apache 2.0 license. If you want to use it for commercial use, it's probably fine but please contact me first.

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	67.64
AI2 Reasoning Challenge (25-Shot)	65.27
HellaSwag (10-Shot)	85.07
MMLU (5-Shot)	63.68
TruthfulQA (0-shot)	54.58
Winogrande (5-shot)	78.77
GSM8k (5-shot)	58.45