Text Generation
Transformers
Safetensors
PyTorch
Nepali
supernova_transformer_v2
supernova
causal-lm
transformer
Instructions to use Supernova11c/Supernova-Transformer-V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Supernova11c/Supernova-Transformer-V2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Supernova11c/Supernova-Transformer-V2")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Supernova11c/Supernova-Transformer-V2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Supernova11c/Supernova-Transformer-V2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Supernova11c/Supernova-Transformer-V2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Supernova11c/Supernova-Transformer-V2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Supernova11c/Supernova-Transformer-V2
- SGLang
How to use Supernova11c/Supernova-Transformer-V2 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 "Supernova11c/Supernova-Transformer-V2" \ --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": "Supernova11c/Supernova-Transformer-V2", "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 "Supernova11c/Supernova-Transformer-V2" \ --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": "Supernova11c/Supernova-Transformer-V2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Supernova11c/Supernova-Transformer-V2 with Docker Model Runner:
docker model run hf.co/Supernova11c/Supernova-Transformer-V2
Download itos.json from Supernova11c/Supernova-Transformer-V2: direct link, hf CLI and curl.
- Browser
- Download file 1.89 kB
-
https://huggingface.co/Supernova11c/Supernova-Transformer-V2/resolve/main/itos.json
- Command line
-
hf download hf://Supernova11c/Supernova-Transformer-V2/itos.json
-
curl -L -o itos.json https://huggingface.co/Supernova11c/Supernova-Transformer-V2/resolve/main/itos.json
1.89 kB
| { | |
| "0": "<PAD>", | |
| "1": "<BOS>", | |
| "2": "<USER>", | |
| "3": "<ASSISTANT>", | |
| "4": "<EOS>", | |
| "5": " ", | |
| "6": "!", | |
| "7": "%", | |
| "8": "'", | |
| "9": ",", | |
| "10": "-", | |
| "11": ".", | |
| "12": "/", | |
| "13": "0", | |
| "14": "1", | |
| "15": "9", | |
| "16": ":", | |
| "17": ";", | |
| "18": "?", | |
| "19": "A", | |
| "20": "B", | |
| "21": "C", | |
| "22": "D", | |
| "23": "E", | |
| "24": "F", | |
| "25": "G", | |
| "26": "H", | |
| "27": "I", | |
| "28": "J", | |
| "29": "M", | |
| "30": "N", | |
| "31": "O", | |
| "32": "P", | |
| "33": "R", | |
| "34": "S", | |
| "35": "T", | |
| "36": "U", | |
| "37": "W", | |
| "38": "Y", | |
| "39": "a", | |
| "40": "b", | |
| "41": "c", | |
| "42": "d", | |
| "43": "e", | |
| "44": "f", | |
| "45": "g", | |
| "46": "h", | |
| "47": "i", | |
| "48": "j", | |
| "49": "k", | |
| "50": "l", | |
| "51": "m", | |
| "52": "n", | |
| "53": "o", | |
| "54": "p", | |
| "55": "q", | |
| "56": "r", | |
| "57": "s", | |
| "58": "t", | |
| "59": "u", | |
| "60": "v", | |
| "61": "w", | |
| "62": "x", | |
| "63": "y", | |
| "64": "z", | |
| "65": "ँ", | |
| "66": "ं", | |
| "67": "ः", | |
| "68": "अ", | |
| "69": "आ", | |
| "70": "इ", | |
| "71": "ई", | |
| "72": "उ", | |
| "73": "ऊ", | |
| "74": "ए", | |
| "75": "ओ", | |
| "76": "औ", | |
| "77": "क", | |
| "78": "ख", | |
| "79": "ग", | |
| "80": "घ", | |
| "81": "ङ", | |
| "82": "च", | |
| "83": "छ", | |
| "84": "ज", | |
| "85": "झ", | |
| "86": "ञ", | |
| "87": "ट", | |
| "88": "ठ", | |
| "89": "ड", | |
| "90": "ढ", | |
| "91": "ण", | |
| "92": "त", | |
| "93": "थ", | |
| "94": "द", | |
| "95": "ध", | |
| "96": "न", | |
| "97": "प", | |
| "98": "फ", | |
| "99": "ब", | |
| "100": "भ", | |
| "101": "म", | |
| "102": "य", | |
| "103": "र", | |
| "104": "ल", | |
| "105": "व", | |
| "106": "श", | |
| "107": "ष", | |
| "108": "स", | |
| "109": "ह", | |
| "110": "ा", | |
| "111": "ि", | |
| "112": "ी", | |
| "113": "ु", | |
| "114": "ू", | |
| "115": "ृ", | |
| "116": "े", | |
| "117": "ै", | |
| "118": "ो", | |
| "119": "ौ", | |
| "120": "्", | |
| "121": "।", | |
| "122": "", | |
| "123": "—", | |
| "124": "‘", | |
| "125": "’", | |
| "126": "“", | |
| "127": "”", | |
| "128": "🌞", | |
| "129": "😄", | |
| "130": "😊" | |
| } |