Text Generation
Transformers
Safetensors
mistral
Merge
beowolx/CodeNinja-1.0-OpenChat-7B
beowolx/MistralHermes-CodePro-7B-v1
Eval Results (legacy)
text-generation-inference
Instructions to use FelixChao/NinjaDolphin-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FelixChao/NinjaDolphin-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="FelixChao/NinjaDolphin-7B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("FelixChao/NinjaDolphin-7B") model = AutoModelForCausalLM.from_pretrained("FelixChao/NinjaDolphin-7B") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use FelixChao/NinjaDolphin-7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "FelixChao/NinjaDolphin-7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FelixChao/NinjaDolphin-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/FelixChao/NinjaDolphin-7B
- SGLang
How to use FelixChao/NinjaDolphin-7B 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 "FelixChao/NinjaDolphin-7B" \ --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": "FelixChao/NinjaDolphin-7B", "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 "FelixChao/NinjaDolphin-7B" \ --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": "FelixChao/NinjaDolphin-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use FelixChao/NinjaDolphin-7B with Docker Model Runner:
docker model run hf.co/FelixChao/NinjaDolphin-7B
NinjaDolphin-7B
NinjaDolphin-7B is a merge of the following models using:
Improving coding ability from FelixChao/WizardDolphin-7B.
HumanEval (uninstructed and no post-process)
| Metric | Value |
|---|---|
| humaneval-python | 52.4390243902439 |
๐งฉ Configuration
models:
- model: FelixChao/WizardDolphin-7B
- model: beowolx/CodeNinja-1.0-OpenChat-7B
parameters:
density: 0.53
weight: 0.3
- model: beowolx/MistralHermes-CodePro-7B-v1
parameters:
density: 0.53
weight: 0.3
merge_method: dare_ties
base_model: FelixChao/WizardDolphin-7B
parameters:
int8_mask: true
dtype: bfloat16
๐ป Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "FelixChao/NinjaDolphin-7B"
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
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 69.74 |
| AI2 Reasoning Challenge (25-Shot) | 65.61 |
| HellaSwag (10-Shot) | 85.35 |
| MMLU (5-Shot) | 64.43 |
| TruthfulQA (0-shot) | 54.94 |
| Winogrande (5-shot) | 80.27 |
| GSM8k (5-shot) | 67.85 |
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Model tree for FelixChao/NinjaDolphin-7B
Evaluation results
- pass@1 on HumanEvalself-reported52.439
