Instructions to use N8Programs/NextTerm-2-5M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use N8Programs/NextTerm-2-5M with Transformers:

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

pipe = pipeline("text-generation", model="N8Programs/NextTerm-2-5M")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("N8Programs/NextTerm-2-5M")
model = AutoModelForCausalLM.from_pretrained("N8Programs/NextTerm-2-5M", device_map="auto")

MLX

How to use N8Programs/NextTerm-2-5M with MLX:

# Make sure mlx-lm is installed
# pip install --upgrade mlx-lm
# if on a CUDA device, also pip install mlx[cuda]

# Generate text with mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("N8Programs/NextTerm-2-5M")

prompt = "Once upon a time in"
text = generate(model, tokenizer, prompt=prompt, verbose=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings
LM Studio

vLLM

How to use N8Programs/NextTerm-2-5M with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "N8Programs/NextTerm-2-5M"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "N8Programs/NextTerm-2-5M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/N8Programs/NextTerm-2-5M

SGLang

How to use N8Programs/NextTerm-2-5M 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 "N8Programs/NextTerm-2-5M" \
    --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": "N8Programs/NextTerm-2-5M",
		"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 "N8Programs/NextTerm-2-5M" \
        --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": "N8Programs/NextTerm-2-5M",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

MLX LM

How to use N8Programs/NextTerm-2-5M with MLX LM:

Generate or start a chat session

# Install MLX LM
uv tool install mlx-lm
# Generate some text
mlx_lm.generate --model "N8Programs/NextTerm-2-5M" --prompt "Once upon a time"

Docker Model Runner
How to use N8Programs/NextTerm-2-5M with Docker Model Runner:
```
docker model run hf.co/N8Programs/NextTerm-2-5M
```
Atomic Chat

NextTerm-2-5M

File size: 1,713 Bytes

515b999

NextTerm-2 evaluation results (released bf16 weights; greedy decoding).
NextTerm-440M / NextTerm-47M / Naive2 rows are from the NextTerm-440M model card.

OEIS-Eval-Neo:
NextTerm-2-440M - 36.25%
NextTerm-2-50M - 31.56%
NextTerm-2-5M - 23.38%
NextTerm-440M - 34.43%
NextTerm-47M - 29.49%

Ryskina & Knight (2021):
NextTerm-2-440M - 66.67%
NextTerm-2-50M - 66.67%
NextTerm-2-5M - 42.11%
NextTerm-440M - 52.63%
NextTerm-47M - 70.18%

M1 Competition 111 MAPE (macro; canonical greedy; lower is better):
Naive2 - 17.7987
NextTerm-2-440M - 17.1105
NextTerm-2-50M - 18.3615
NextTerm-2-5M - 20.8527
NextTerm-440M - 17.6239
NextTerm-47M - 18.7621

M1 Competition 111 by frequency (macro MAPE):
Naive2 - monthly 17.3871 / quarterly 19.5958 / yearly 17.1314
NextTerm-2-440M - monthly 18.5442 / quarterly 16.6647 / yearly 12.7485
NextTerm-2-50M - monthly 20.7720 / quarterly 16.6578 / yearly 12.1251
NextTerm-2-5M - monthly 22.3369 / quarterly 23.4687 / yearly 12.7977
NextTerm-440M - monthly 18.3407 / quarterly 19.0475 / yearly 13.5498
NextTerm-47M - monthly 21.2719 / quarterly 16.0270 / yearly 13.3741

Polynomial continuation evals (accuracy; 200 samples per k):
Arithmetic (k=2-25): NextTerm-2-440M - 96.15%; NextTerm-2-50M - 96.31%; NextTerm-2-5M - 78.21%; NextTerm-440M - 94.38%; NextTerm-47M - 94.15%
Quadratic (k=3-25): NextTerm-2-440M - 94.39%; NextTerm-2-50M - 84.11%; NextTerm-2-5M - 23.87%; NextTerm-440M - 86.39%; NextTerm-47M - 81.07%
Cubic (k=4-25): NextTerm-2-440M - 88.70%; NextTerm-2-50M - 63.95%; NextTerm-2-5M - 1.89%; NextTerm-440M - 75.20%; NextTerm-47M - 37.43%
Quartic (k=5-25): NextTerm-2-440M - 83.74%; NextTerm-2-50M - 47.86%; NextTerm-2-5M - 0.50%; NextTerm-440M - 67.83%; NextTerm-47M - 15.17%