Text Generation
Transformers
PyTorch
Safetensors
English
gpt_neox
HelpingAI
vortex
Eval Results (legacy)
text-generation-inference
Instructions to use OEvortex/vortex-3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OEvortex/vortex-3b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="OEvortex/vortex-3b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("OEvortex/vortex-3b") model = AutoModelForCausalLM.from_pretrained("OEvortex/vortex-3b") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use OEvortex/vortex-3b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OEvortex/vortex-3b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OEvortex/vortex-3b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/OEvortex/vortex-3b
- SGLang
How to use OEvortex/vortex-3b 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 "OEvortex/vortex-3b" \ --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": "OEvortex/vortex-3b", "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 "OEvortex/vortex-3b" \ --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": "OEvortex/vortex-3b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use OEvortex/vortex-3b with Docker Model Runner:
docker model run hf.co/OEvortex/vortex-3b
| language: | |
| - en | |
| license: other | |
| tags: | |
| - HelpingAI | |
| - vortex | |
| datasets: | |
| - OEvortex/Vortex-50k | |
| license_name: helpingai | |
| license_link: LICENSE.md | |
| pipeline_tag: text-generation | |
| model-index: | |
| - name: vortex-3b | |
| 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: 31.91 | |
| name: normalized accuracy | |
| source: | |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OEvortex/vortex-3b | |
| 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: 56.89 | |
| name: normalized accuracy | |
| source: | |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OEvortex/vortex-3b | |
| 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: 27.32 | |
| name: accuracy | |
| source: | |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OEvortex/vortex-3b | |
| 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: 37.39 | |
| source: | |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OEvortex/vortex-3b | |
| 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: 60.14 | |
| name: accuracy | |
| source: | |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OEvortex/vortex-3b | |
| 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: 0.91 | |
| name: accuracy | |
| source: | |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=OEvortex/vortex-3b | |
| name: Open LLM Leaderboard | |
|  | |
| **Model Overview** | |
| vortex-3b is a 2.78 billion parameter causal language model created by OEvortex that is derived from EleutherAI's Pythia-2.8b and fine-tuned on Vortex-50k dataset' | |
| ```python | |
| from transformers import pipeline | |
| # Initialize the pipeline | |
| pipe = pipeline("text-generation", model="OEvortex/vortex-3b") | |
| # Use the pipeline | |
| text = "Once upon a time" | |
| generated_text = pipe(text, max_length=100, do_sample=True)[0]['generated_text'] | |
| print(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_OEvortex__vortex-3b) | |
| | Metric | vortex 3b | vortex 3b-v2 | dolly-v2-3b | pythia-2.8b-deduped | | |
| |---------|----------:|-------------:|------------------:|----------------------------------:| | |
| | Avg. | 35.76 | 37.46 | 25.26 | 36.72 | | |
| | AI2 Reasoning Challenge (25-Shot) | 31.91 | 39.68 | 22.83 | 36.26 | | |
| | HellaSwag (10-Shot) | 56.89 | 65.04 | 26.55 | 60.66 | | |
| | MMLU (5-Shot) | 27.32 | 25.09 | 24.7 | 26.78 | | |
| | TruthfulQA (0-shot) | 37.39 | 33.80 | 0 | 35.56 | | |
| | Winogrande (5-shot) | 60.14 | 59.12 | 59.43 | 60.22 | | |
| | GSM8k (5-shot) | 0.91 | 2.05 | 1.86 | 0.83 | | |