Text Generation
Transformers
Safetensors
PyTorch
English
bananamind2_pro
causal-lm
language-model
base-model
small-language-model
bananamind
bananamind2
bananamind2-pro
preview-checkpoint
digit-tokenizer
custom-code
trust-remote-code
custom-architecture
custom_code
Instructions to use GGMLGuy/BananaMind-2-Pro-Preview-backup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GGMLGuy/BananaMind-2-Pro-Preview-backup with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="GGMLGuy/BananaMind-2-Pro-Preview-backup", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("GGMLGuy/BananaMind-2-Pro-Preview-backup", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use GGMLGuy/BananaMind-2-Pro-Preview-backup with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "GGMLGuy/BananaMind-2-Pro-Preview-backup" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "GGMLGuy/BananaMind-2-Pro-Preview-backup", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/GGMLGuy/BananaMind-2-Pro-Preview-backup
- SGLang
How to use GGMLGuy/BananaMind-2-Pro-Preview-backup 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 "GGMLGuy/BananaMind-2-Pro-Preview-backup" \ --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": "GGMLGuy/BananaMind-2-Pro-Preview-backup", "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 "GGMLGuy/BananaMind-2-Pro-Preview-backup" \ --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": "GGMLGuy/BananaMind-2-Pro-Preview-backup", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use GGMLGuy/BananaMind-2-Pro-Preview-backup with Docker Model Runner:
docker model run hf.co/GGMLGuy/BananaMind-2-Pro-Preview-backup
| { | |
| "source_checkpoint": "runs/bananamind2-pro/checkpoints/step_095999.pt", | |
| "step": 95999, | |
| "optimizer_steps_completed": 96000, | |
| "tokens_seen": 51904512000, | |
| "micro_batch": 4, | |
| "grad_accum": 44, | |
| "repo_id": "BananaMind/BananaMind-2-Pro-Preview", | |
| "format": "huggingface_transformers_remote_code" | |
| } | |