Text Generation
Transformers
PyTorch
Indonesian
English
code
mesosfer
bear-ai
llama-architecture
causal-lm
Instructions to use Dummy9898/bear-240m-cpt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dummy9898/bear-240m-cpt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Dummy9898/bear-240m-cpt")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Dummy9898/bear-240m-cpt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Dummy9898/bear-240m-cpt with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Dummy9898/bear-240m-cpt" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Dummy9898/bear-240m-cpt", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Dummy9898/bear-240m-cpt
- SGLang
How to use Dummy9898/bear-240m-cpt 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 "Dummy9898/bear-240m-cpt" \ --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": "Dummy9898/bear-240m-cpt", "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 "Dummy9898/bear-240m-cpt" \ --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": "Dummy9898/bear-240m-cpt", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Dummy9898/bear-240m-cpt with Docker Model Runner:
docker model run hf.co/Dummy9898/bear-240m-cpt
| { | |
| "timestamp": "2026-08-16T01:57:17.410981", | |
| "checkpoint": "storage/models/bear_final.pt", | |
| "device": "cpu", | |
| "stages": { | |
| "cpt": { | |
| "summary": { | |
| "avg_loss": 1.8693425178527832, | |
| "pattern_match_rate": 60.0, | |
| "task_count": 5 | |
| }, | |
| "details": [ | |
| { | |
| "id": "hf_cpt_humaneval_01", | |
| "category": "code_python", | |
| "loss": 1.0997084379196167, | |
| "ppl": 3.0032902507280093, | |
| "bpb": 0.46254924484267623, | |
| "syntax_pattern_match": true, | |
| "generated_sample": "def is_prime(n: int) -> bool:\n \"\"\"Return True if a given number is prime, and False otherwise.\n >>> is_prime(10" | |
| }, | |
| { | |
| "id": "hf_cpt_gsm8k_01", | |
| "category": "math_reasoning", | |
| "loss": 1.5855170488357544, | |
| "ppl": 4.881814862765376, | |
| "bpb": 0.6668855928863694, | |
| "syntax_pattern_match": true, | |
| "generated_sample": "48 total clips and 48 \u00d7 48 = 48.\nStep 2: Natalia sold 48 \u00d7 48 = 48 total clips" | |
| }, | |
| { | |
| "id": "hf_cpt_latex_math_01", | |
| "category": "latex_equations", | |
| "loss": 1.7661380767822266, | |
| "ppl": 5.848224300451033, | |
| "bpb": 0.7428567477839328, | |
| "syntax_pattern_match": false, | |
| "generated_sample": "\\frac{1}{\\sqrt{4\\pi}} \\int_{-\\infty}^{\\infty} e^{-x^2} \\, dx = \\frac{1}{\\" | |
| }, | |
| { | |
| "id": "hf_cpt_powershell_01", | |
| "category": "terminal_powershell", | |
| "loss": 3.6109378337860107, | |
| "ppl": 37.0007370895879, | |
| "bpb": 1.5187994477438524, | |
| "syntax_pattern_match": false, | |
| "generated_sample": "# - Name: A\n# - Name: C\n# - Name: D\n# - Name: E\n# - Name" | |
| }, | |
| { | |
| "id": "hf_cpt_typescript_01", | |
| "category": "code_typescript", | |
| "loss": 1.2844111919403076, | |
| "ppl": 3.6125402380616927, | |
| "bpb": 0.5402372178059954, | |
| "syntax_pattern_match": true, | |
| "generated_sample": "return {\n getDefaultConfig(): BearModelConfig\n }\n}\n\nfunction createBuildConfig(): BearModelConfig {\n return {\n getBuild" | |
| } | |
| ] | |
| } | |
| } | |
| } |