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")

# 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 /teacher_decoding.json

N8Programs

Expand BestTerm model card with benchmark comparisons and reproducibility

6c2b324 verified 2 days ago

Raw

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1.14 kB

	{
	"model": "N8Programs/BestTerm-440M-Checkpts",
	"table": {
	"greedy": "38/57",
	"greedy_restricted": "38/57",
	"beam4_t64": "40/57",
	"beam4_t160": "40/57",
	"beam8_t64": "40/57",
	"beam8_t160": "40/57",
	"beam16_t64": "ERROR",
	"beam16_t160": "ERROR",
	"vote32_T0.7": "31/57",
	"rerank32_T0.7_h1_total": "38/57",
	"rerank32_T0.7_h1_mean": "39/57",
	"rerank32_T0.7_h2_total": "39/57",
	"rerank32_T0.7_h2_mean": "39/57",
	"rerank32_T0.7_h4_total": "39/57",
	"rerank32_T0.7_h4_mean": "39/57",
	"rerank32_T0.7_h8_total": "38/57",
	"rerank32_T0.7_h8_mean": "40/57",
	"rerank32_T0.7_h16_total": "37/57",
	"rerank32_T0.7_h16_mean": "38/57",
	"vote32_T1.0": "35/57",
	"rerank32_T1.0_h1_total": "38/57",
	"rerank32_T1.0_h1_mean": "39/57",
	"rerank32_T1.0_h2_total": "39/57",
	"rerank32_T1.0_h2_mean": "39/57",
	"rerank32_T1.0_h4_total": "38/57",
	"rerank32_T1.0_h4_mean": "38/57",
	"rerank32_T1.0_h8_total": "40/57",
	"rerank32_T1.0_h8_mean": "40/57",
	"rerank32_T1.0_h16_total": "39/57",
	"rerank32_T1.0_h16_mean": "40/57"
	},
	"num_samples": 32
	}