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_oeis.json

N8Programs

Expand BestTerm model card with benchmark comparisons and reproducibility

6c2b324 verified 30 days ago

Raw History Blame Contribute Delete

500 Bytes

{
  "data_path": "oeis_val_neo.jsonl",
  "model": "base_model",
  "output": "base_oeis_eval_neo_mlx_full_b512.jsonl",
  "documents": 19034,
  "evaluated": 19034,
  "expected_evaluated": 19034,
  "skipped_long": 0,
  "parsed": 19033,
  "correct": 6555,
  "accuracy": 0.3443837343700746,
  "max_new_tokens": 196,
  "max_context_tokens": 4096,
  "batch_size": 128,
  "restrict_digit_comma_eos": false,
  "restrict_integer_comma_eos": false,
  "allowed_token_ids": null,
  "seconds": 23.02982224902371
}

	{
	"data_path": "oeis_val_neo.jsonl",
	"model": "base_model",
	"output": "base_oeis_eval_neo_mlx_full_b512.jsonl",
	"documents": 19034,
	"evaluated": 19034,
	"expected_evaluated": 19034,
	"skipped_long": 0,
	"parsed": 19033,
	"correct": 6555,
	"accuracy": 0.3443837343700746,
	"max_new_tokens": 196,
	"max_context_tokens": 4096,
	"batch_size": 128,
	"restrict_digit_comma_eos": false,
	"restrict_integer_comma_eos": false,
	"allowed_token_ids": null,
	"seconds": 23.02982224902371
	}