Text Generation
Transformers
Safetensors
Lithuanian
llama
blkt
causal-lm
pretraining
lithuanian
llama3
text-generation-inference
Instructions to use VSSA-SDSA/LT_AI_DLKVM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VSSA-SDSA/LT_AI_DLKVM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="VSSA-SDSA/LT_AI_DLKVM")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("VSSA-SDSA/LT_AI_DLKVM") model = AutoModelForCausalLM.from_pretrained("VSSA-SDSA/LT_AI_DLKVM") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use VSSA-SDSA/LT_AI_DLKVM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "VSSA-SDSA/LT_AI_DLKVM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "VSSA-SDSA/LT_AI_DLKVM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/VSSA-SDSA/LT_AI_DLKVM
- SGLang
How to use VSSA-SDSA/LT_AI_DLKVM 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 "VSSA-SDSA/LT_AI_DLKVM" \ --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": "VSSA-SDSA/LT_AI_DLKVM", "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 "VSSA-SDSA/LT_AI_DLKVM" \ --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": "VSSA-SDSA/LT_AI_DLKVM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use VSSA-SDSA/LT_AI_DLKVM with Docker Model Runner:
docker model run hf.co/VSSA-SDSA/LT_AI_DLKVM
| { | |
| "@context": "https://semiceu.github.io/MLDCAT-AP/releases/3.0.0/context/mldcat-ap.jsonld", | |
| "@type": "it6:MachineLearningModel", | |
| "@id": "https://example.lt/model/DVLKM", | |
| "dct:identifier": "DVLKM", | |
| "dct:title": { | |
| "@value": "LT generavimo modelis", | |
| "@language": "lt" | |
| }, | |
| "dct:description": { | |
| "@value": "LT generavimo modelis", | |
| "@language": "lt" | |
| }, | |
| "dct:created": "2026-04-15 00:00:00", | |
| "it6:version": "1.0", | |
| "dct:publisher": { | |
| "@type": "foaf:Agent", | |
| "foaf:name": "VSSA" | |
| }, | |
| "dct:creator": { | |
| "@type": "foaf:Agent", | |
| "foaf:name": "UAB Neurotechnology" | |
| }, | |
| "dct:rightsHolder": { | |
| "@type": "foaf:Agent", | |
| "foaf:name": "VSSA" | |
| }, | |
| "dct:license": { | |
| "@id": "MIT" | |
| }, | |
| "it6:intendedUse": [ | |
| { | |
| "@value": "modelis skirtas teksyto generavimui", | |
| "@language": "lt" | |
| } | |
| ], | |
| "dct:language": [ | |
| { | |
| "@value": "lt" | |
| } | |
| ], | |
| "it6:modelArchitecture": [ | |
| { | |
| "@value": "transformer" | |
| } | |
| ], | |
| "it6:hasInputModality": [ | |
| { | |
| "@value": "text" | |
| } | |
| ], | |
| "it6:hasOutputModality": [ | |
| { | |
| "@value": "text" | |
| } | |
| ], | |
| "dcat:landingPage": { | |
| "@id": "Huggingface" | |
| }, | |
| "it6:trainedOn": [ | |
| { | |
| "@id": "https://example.lt/dataset/BLKT" | |
| } | |
| ], | |
| "it6:hasFile": [ | |
| { | |
| "@type": "it6:File", | |
| "@id": "https://example.lt/file/dvlkm", | |
| "dct:title": { | |
| "@value": "DLKVM", | |
| "@language": "lt" | |
| }, | |
| "dct:format": { | |
| "@value": "application/octet-stream" | |
| }, | |
| "dcat:accessURL": { | |
| "@id": "Huggingface" | |
| }, | |
| "it6:url": { | |
| "@id": "Huggingface" | |
| } | |
| } | |
| ] | |
| } |