Instructions to use NathMen12/Nyvex-Small-1.2-Beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use NathMen12/Nyvex-Small-1.2-Beta with Transformers:

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

pipe = pipeline("text-generation", model="NathMen12/Nyvex-Small-1.2-Beta")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("NathMen12/Nyvex-Small-1.2-Beta")
model = AutoModelForCausalLM.from_pretrained("NathMen12/Nyvex-Small-1.2-Beta", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use NathMen12/Nyvex-Small-1.2-Beta with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "NathMen12/Nyvex-Small-1.2-Beta"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "NathMen12/Nyvex-Small-1.2-Beta",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/NathMen12/Nyvex-Small-1.2-Beta

SGLang

How to use NathMen12/Nyvex-Small-1.2-Beta 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 "NathMen12/Nyvex-Small-1.2-Beta" \
    --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": "NathMen12/Nyvex-Small-1.2-Beta",
		"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 "NathMen12/Nyvex-Small-1.2-Beta" \
        --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": "NathMen12/Nyvex-Small-1.2-Beta",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use NathMen12/Nyvex-Small-1.2-Beta with Docker Model Runner:
```
docker model run hf.co/NathMen12/Nyvex-Small-1.2-Beta
```

Nyvex-Small-1.2-Beta

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---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: Nyvex-Small-1.2-Beta
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Nyvex-Small-1.2-Beta

This model was trained from scratch on an unknown dataset.

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAFACTOR and the args are:
No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1

### Training results



### Framework versions

- Transformers 5.9.0
- Pytorch 2.8.0+cu128
- Datasets 4.8.5
- Tokenizers 0.22.2