Instructions to use TheNormsOfIntelligence/ATC_Nima_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TheNormsOfIntelligence/ATC_Nima_Model with Transformers:

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

pipe = pipeline("text-generation", model="TheNormsOfIntelligence/ATC_Nima_Model")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("TheNormsOfIntelligence/ATC_Nima_Model", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use TheNormsOfIntelligence/ATC_Nima_Model with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/TheNormsOfIntelligence/ATC_Nima_Model

SGLang

How to use TheNormsOfIntelligence/ATC_Nima_Model 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 "TheNormsOfIntelligence/ATC_Nima_Model" \
    --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": "TheNormsOfIntelligence/ATC_Nima_Model",
		"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 "TheNormsOfIntelligence/ATC_Nima_Model" \
        --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": "TheNormsOfIntelligence/ATC_Nima_Model",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use TheNormsOfIntelligence/ATC_Nima_Model with Docker Model Runner:
```
docker model run hf.co/TheNormsOfIntelligence/ATC_Nima_Model
```

ATC_Nima_Model / requirements.txt

TheNormsOfIntelligence

Restructure into nima_unified package + add model card

7caf3c0 verified 18 days ago

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	# ── Core deep-learning stack ──
	torch>=2.1.0
	transformers>=4.43.0
	tokenizers>=0.19.0
	accelerate>=0.30.0
	safetensors>=0.4.0

	# ── Fine-tuning ──
	peft>=0.10.0
	datasets>=2.18.0

	# ── Numerics / system ──
	numpy>=1.24.0
	psutil>=5.9.0

	# ── Voice (OmniVoice v3 — optional but recommended) ──
	# Uncomment to enable Whisper ASR + XTTS neural TTS:
	# openai-whisper>=20231117
	# TTS>=0.22.0
	# sounddevice>=0.4.6
	# soundfile>=0.12.1

	# ── Benchmarking / dashboard ──
	scikit-learn>=1.3.0
	tqdm>=4.65.0

	# ── Optional: HF Hub push ──
	huggingface_hub>=0.23.0