Text Generation
Transformers
Safetensors
Polish
koliber
polish
causal-lm
base-model
from-scratch
gqa
rope
swiglu
preview
custom_code
Instructions to use OrisTeam/Koliber-v1.0-Base-Preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OrisTeam/Koliber-v1.0-Base-Preview with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="OrisTeam/Koliber-v1.0-Base-Preview", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("OrisTeam/Koliber-v1.0-Base-Preview", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use OrisTeam/Koliber-v1.0-Base-Preview with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OrisTeam/Koliber-v1.0-Base-Preview" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OrisTeam/Koliber-v1.0-Base-Preview", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/OrisTeam/Koliber-v1.0-Base-Preview
- SGLang
How to use OrisTeam/Koliber-v1.0-Base-Preview 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 "OrisTeam/Koliber-v1.0-Base-Preview" \ --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": "OrisTeam/Koliber-v1.0-Base-Preview", "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 "OrisTeam/Koliber-v1.0-Base-Preview" \ --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": "OrisTeam/Koliber-v1.0-Base-Preview", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use OrisTeam/Koliber-v1.0-Base-Preview with Docker Model Runner:
docker model run hf.co/OrisTeam/Koliber-v1.0-Base-Preview
| { | |
| "architectures": [ | |
| "KoliberForCausalLM" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_koliber.KoliberConfig", | |
| "AutoModelForCausalLM": "modeling_koliber.KoliberForCausalLM" | |
| }, | |
| "bos_token_id": 2, | |
| "eos_token_id": 3, | |
| "hidden_size": 768, | |
| "intermediate_size": 3072, | |
| "max_position_embeddings": 1536, | |
| "model_type": "koliber", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "num_key_value_heads": 2, | |
| "pad_token_id": 0, | |
| "rms_norm_eps": 1e-06, | |
| "rope_theta": 10000.0, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.13.0", | |
| "use_cache": false, | |
| "vocab_size": 32000 | |
| } | |