Text Generation
Transformers
Safetensors
qwen3
oeis
integer-sequences
sequence-modeling
slerp
text-generation-inference
Instructions to use N8Programs/BestTerm-440M-Checkpts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
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
Download benchmarks/hot500_training.json from N8Programs/BestTerm-440M-Checkpts: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/N8Programs/BestTerm-440M-Checkpts/resolve/main/benchmarks/hot500_training.json
- Command line
-
hf download hf://N8Programs/BestTerm-440M-Checkpts/benchmarks/hot500_training.json
-
curl -L -o hot500_training.json https://huggingface.co/N8Programs/BestTerm-440M-Checkpts/resolve/main/benchmarks/hot500_training.json
3.64 kB
| { | |
| "checkpoint": "checkpoint_tokens_000500020611.pt", | |
| "trainer_state": { | |
| "completed_steps": 20486, | |
| "train_tokens_seen": 500020611, | |
| "last_loss": 0.759232759475708 | |
| }, | |
| "checkpoint_args": { | |
| "data": "oeis_train_bfile_prefix4096.packed", | |
| "model_backend": "custom", | |
| "param_dtype": "fp32", | |
| "weight_update_mode": "bf16_live_fp32_master", | |
| "batch_size": 1, | |
| "seq_len": 4096, | |
| "steps": 5, | |
| "warmup_steps": 2, | |
| "target_tokens": 754629901, | |
| "max_steps": 0, | |
| "batch_mode": "bucketed", | |
| "pad_to_seq_len": false, | |
| "index_dir": "oeis_train_bfile_prefix4096.packed.idx", | |
| "bucket_tokens_per_batch": 16384, | |
| "bucket_token_budget_spec": "512:32768,*:24576", | |
| "bucket_max_batch_size": 512, | |
| "bucket_pad_multiple": 8, | |
| "bucket_pad_to_upper": true, | |
| "bucket_replacement": false, | |
| "bucket_repeat_epochs": true, | |
| "bucket_sampling": "token_mass", | |
| "vocab_mode": "oeis", | |
| "hidden_size": 1024, | |
| "intermediate_size": 3072, | |
| "num_hidden_layers": 28, | |
| "num_attention_heads": 16, | |
| "num_key_value_heads": 8, | |
| "head_dim": 0, | |
| "compile": true, | |
| "compile_mode": "reduce-overhead", | |
| "compile_dynamic": true, | |
| "compile_skip_dynamic_cudagraphs": true, | |
| "prewarm_bucket_shapes": true, | |
| "prewarm_bucket_passes": 2, | |
| "prewarm_restore_state": true, | |
| "prewarm_verify_restore": false, | |
| "prewarm_update_optimizer": false, | |
| "prewarm_materialize_optimizer_state": true, | |
| "gradient_checkpointing": false, | |
| "native_gqa": true, | |
| "amp": true, | |
| "lr": 0.0003, | |
| "optimizer_mode": "torch_muon_hybrid", | |
| "adamw_lr": 0.0001, | |
| "muon_lr": 0.01, | |
| "body_lr_mult": 1.0, | |
| "adamw_weight_decay": 0.01, | |
| "muon_weight_decay": 0.0, | |
| "muon_momentum": 0.95, | |
| "muon_ns_steps": 5, | |
| "muon_adjust_lr_fn": "", | |
| "no_muon_nesterov": false, | |
| "lr_schedule": "warmup_cosine_cooldown", | |
| "lr_total_tokens": 754629901, | |
| "lr_warmup_tokens": 0, | |
| "lr_warmup_fraction": 0.005, | |
| "lr_decay_end_fraction": 0.95, | |
| "lr_peak_factor": 1.0, | |
| "lr_min_factor": 0.1, | |
| "lr_final_factor": 0.0, | |
| "checkpoint_dir": "checkpoints", | |
| "checkpoint_every_tokens": 250000000, | |
| "checkpoint_every_steps": 0, | |
| "keep_last_checkpoints": 4, | |
| "resume": "", | |
| "init_from_hf_dir": "base_model", | |
| "save_final": true, | |
| "trim_final_batch": true, | |
| "allow_token_overshoot": false, | |
| "val_data": "oeis_val_decontam.jsonl", | |
| "val_format": "jsonl", | |
| "val_index_dir": "", | |
| "val_every_tokens": 250000000, | |
| "val_every_steps": 0, | |
| "val_batches": 128, | |
| "val_batch_size": 32, | |
| "val_max_examples": 0, | |
| "val_max_context_tokens": 4096, | |
| "oeis_eval_data": "", | |
| "oeis_eval_every_tokens": 0, | |
| "oeis_eval_every_steps": 0, | |
| "oeis_eval_batch_size": 64, | |
| "oeis_eval_max_examples": 0, | |
| "oeis_eval_max_new_tokens": 20, | |
| "oeis_eval_max_context_tokens": 0, | |
| "oeis_eval_collect_examples": 3, | |
| "oeis_eval_generation_backend": "legacy", | |
| "expected_loss_tokens": 754629901, | |
| "safe_preflight": true, | |
| "allow_synthetic_only": false, | |
| "allow_replacement_sampling": false, | |
| "preflight_only": false, | |
| "wandb": true, | |
| "wandb_project": "oeis-massive", | |
| "wandb_entity": "n8programs", | |
| "wandb_run_name": "nextterm-440m-bfile-only-1epoch-20260701-gqa-lrpeak100", | |
| "wandb_id": "nextterm440m-bfile-only-1epoch-20260701-gqa-lrpeak100", | |
| "wandb_resume": "allow", | |
| "wandb_mode": "online", | |
| "wandb_anonymous": "", | |
| "wandb_tags": "bfile-only,continued-pretraining,440m,no-synth,invlen-repair,lrpeak100", | |
| "log_every_steps": 10, | |
| "seed": 0, | |
| "report_json": "report.json" | |
| } | |
| } | |