Instructions to use N8Programs/BestTerm-440M-Checkpts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use N8Programs/BestTerm-440M-Checkpts with Transformers:

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

pipe = pipeline("text-generation", model="N8Programs/BestTerm-440M-Checkpts")

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

tokenizer = AutoTokenizer.from_pretrained("N8Programs/BestTerm-440M-Checkpts")
model = AutoModelForCausalLM.from_pretrained("N8Programs/BestTerm-440M-Checkpts", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use N8Programs/BestTerm-440M-Checkpts with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "N8Programs/BestTerm-440M-Checkpts"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "N8Programs/BestTerm-440M-Checkpts",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/N8Programs/BestTerm-440M-Checkpts

SGLang

How to use N8Programs/BestTerm-440M-Checkpts 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/BestTerm-440M-Checkpts" \
    --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/BestTerm-440M-Checkpts",
		"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/BestTerm-440M-Checkpts" \
        --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/BestTerm-440M-Checkpts",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use N8Programs/BestTerm-440M-Checkpts with Docker Model Runner:
```
docker model run hf.co/N8Programs/BestTerm-440M-Checkpts
```

BestTerm-440M-Checkpts / benchmarks /original_base_m1.json

N8Programs

Expand BestTerm model card with benchmark comparisons and reproducibility

6c2b324 verified 23 days ago

Raw History Blame Contribute Delete

1.58 kB

	{
	"data_path": "m1_competition_111.jsonl",
	"model": "base_model",
	"output": "base_m1_competition111_mlx_b64.jsonl",
	"series_loaded": 111,
	"series_evaluated": 111,
	"skipped_long": 0,
	"max_context_tokens": 2048,
	"max_new_tokens": 1024,
	"batch_size": 64,
	"missing_policy": "zero",
	"suppress_eos_until_horizon": true,
	"seconds": 4.492863438004861,
	"series_count": 111,
	"horizon_counts": {
	"6": 20,
	"8": 23,
	"18": 68
	},
	"model_macro_mape": 17.623926615357572,
	"model_median_series_mape": 13.829597418172249,
	"model_point_mape": 18.049557899117335,
	"naive2_macro_mape": 17.798673616724457,
	"naive2_point_mape": 17.63296459764299,
	"parsed_full_series": 111,
	"total_missing_terms": 0,
	"malformed_series": 0,
	"by_period": {
	"MONTHLY": {
	"series_count": 68,
	"model_macro_mape": 18.340690204852887,
	"model_point_mape": 18.340690204852887,
	"naive2_macro_mape": 17.387066649846865,
	"naive2_point_mape": 17.387066649846865,
	"parsed_full_series": 68
	},
	"QUARTERLY": {
	"series_count": 23,
	"model_macro_mape": 19.047524714417133,
	"model_point_mape": 19.047524714417133,
	"naive2_macro_mape": 19.59580196054251,
	"naive2_point_mape": 19.59580196054251,
	"parsed_full_series": 23
	},
	"YEARLY": {
	"series_count": 20,
	"model_macro_mape": 13.549792597154996,
	"model_point_mape": 13.549792597154996,
	"naive2_macro_mape": 17.131439708717515,
	"naive2_point_mape": 17.131439708717515,
	"parsed_full_series": 20
	}
	}
	}