Instructions to use Omarrran/ks-byte-lm-spacebyte-transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Omarrran/ks-byte-lm-spacebyte-transformers with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Omarrran/ks-byte-lm-spacebyte-transformers", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("Omarrran/ks-byte-lm-spacebyte-transformers", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Omarrran/ks-byte-lm-spacebyte-transformers with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Omarrran/ks-byte-lm-spacebyte-transformers"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Omarrran/ks-byte-lm-spacebyte-transformers",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Omarrran/ks-byte-lm-spacebyte-transformers

SGLang

How to use Omarrran/ks-byte-lm-spacebyte-transformers 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 "Omarrran/ks-byte-lm-spacebyte-transformers" \
    --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": "Omarrran/ks-byte-lm-spacebyte-transformers",
		"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 "Omarrran/ks-byte-lm-spacebyte-transformers" \
        --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": "Omarrran/ks-byte-lm-spacebyte-transformers",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Omarrran/ks-byte-lm-spacebyte-transformers with Docker Model Runner:
```
docker model run hf.co/Omarrran/ks-byte-lm-spacebyte-transformers
```

ks-byte-lm-spacebyte-transformers / ksbyte /normalize /_upstream /constants.py

Omarrran

Add Transformers-compatible ks_byte_lm SpaceByte release

45121cf verified about 1 month ago

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7.27 kB

	from typing import Dict, List, FrozenSet


	KASHMIRI_CHARACTER_MAPPING: Dict[str, List[str]] = {'آ': ['ﺁ', 'ﺂ'],
	'أ': ['ﺃ'],
	'ا': ['ﺍ', 'ﺎ'],
	'ب': ['ﺏ', 'ﺐ', 'ﺑ', 'ﺒ'],
	'پ': ['ﭖ', 'ﭘ', 'ﭙ', ],
	'ت': ['ﺕ', 'ﺖ', 'ﺗ', 'ﺘ'],
	'ٹ': ['ﭦ', 'ﭧ', 'ﭨ', 'ﭩ'],
	'ث': ['ﺛ', 'ﺜ', 'ﺚ'],
	'ج': ['ﺝ', 'ﺞ', 'ﺟ', 'ﺠ'],
	'ح': ['ﺡ', 'ﺣ', 'ﺤ', 'ﺢ'],
	'خ': ['ﺧ', 'ﺨ', 'ﺦ'],
	'د': ['ﺩ', 'ﺪ'],
	'ذ': ['ﺬ', 'ﺫ'],
	'ر': ['ﺭ', 'ﺮ'],
	'ز': ['ﺯ', 'ﺰ', ],
	'س': ['ﺱ', 'ﺲ', 'ﺳ', 'ﺴ', ],
	'ش': ['ﺵ', 'ﺶ', 'ﺷ', 'ﺸ'],
	'ص': ['ﺹ', 'ﺺ', 'ﺻ', 'ﺼ', ],
	'ض': ['ﺽ', 'ﺾ', 'ﺿ', 'ﻀ'],
	'ط': ['ﻃ', 'ﻄ'],
	'ظ': ['ﻅ', 'ﻇ', 'ﻈ'],
	'ع': ['ﻉ', 'ﻊ', 'ﻋ', 'ﻌ', ],
	'غ': ['ﻍ', 'ﻏ', 'ﻐ', ],
	'ف': ['ﻑ', 'ﻒ', 'ﻓ', 'ﻔ', ],
	'ق': ['ﻕ', 'ﻖ', 'ﻗ', 'ﻘ', ],
	'ل': ['ﻝ', 'ﻞ', 'ﻟ', 'ﻠ', ],
	'م': ['ﻡ', 'ﻢ', 'ﻣ', 'ﻤ', ],
	'ن': ['ﻥ', 'ﻦ', 'ﻧ', 'ﻨ', ],
	'چ': ['ﭺ', 'ﭻ', 'ﭼ', 'ﭽ'],
	'ڈ': ['ﮈ', 'ﮉ'],
	'ڑ': ['ﮍ', 'ﮌ'],
	'ژ': ['ﮋ', ],
	'ک': ['ﮎ', 'ﮏ', 'ﮐ', 'ﮑ', 'ﻛ', 'ك'],
	'گ': ['ﮒ', 'ﮓ', 'ﮔ', 'ﮕ'],
	'ں': ['ﮞ', 'ﮟ'],
	'و': ['ﻮ', 'ﻭ', 'ﻮ', ],
	'ؤ': ['ﺅ'],
	'ھ': ['ﮪ', 'ﮬ', 'ﮭ', 'ﻬ', 'ﻫ', 'ﮫ'],
	'ہ': ['ﻩ', 'ﮦ', 'ﻪ', 'ﮧ', 'ﮩ', 'ﮨ', 'ه', ],
	'ۂ': [],
	'ۃ': ['ة'],
	'ء': ['ﺀ'],
	'ی': ['ﯼ', 'ى', 'ﯽ', 'ﻰ', 'ﻱ', 'ﻲ', 'ﯾ', 'ﯿ', 'ي'],
	'ئ': ['ﺋ', 'ﺌ', ],
	'ے': ['ﮮ', 'ﮯ', 'ﻳ', 'ﻴ', ],
	'ۓ': [],
	'۰': ['٠'],
	'۱': ['١'],
	'۲': ['٢'],
	'۳': ['٣'],
	'۴': ['٤'],
	'۵': ['٥'],
	'۶': ['٦'],
	'۷': ['٧'],
	'۸': ['٨'],
	'۹': ['٩'],
	'۔': [],
	'؟': [],
	'٫': [],
	'،': [],
	'لا': ['ﻻ', 'ﻼ'],
	'': ['ـ'],
	'ژ':['ـژ', 'ـژ'],
	'ؠ':['ـؠ','\u06ea', '\u066e\u06ea', 'ؠـ', 'ـؠـ', ],
	'ۄ':['\u06c5'],
	' ' : ['\u200C'], # NOT A CHARACTER, HANDLING ZWNJ by Replacing with space
	'ۍ' : []

	}

	PUNCTUATION_MAP: Dict[str, List[str]] = {
	'"': ['„', '“', '”', "''", '´´'],
	'-': ['–'],
	' - ': ['—'],
	"'": ['´', '‘', '‚', '’'],
	'...': ['…'],

	}

	ENG_KASHMIRI_DIGITS_MAP: Dict = {
	'0': ['۰'],
	'1': ['۱'],
	'2': ['۲'],
	'3': ['۳'],
	'4': ['۴'],
	'5': ['۵'],
	'6': ['۶'],
	'7': ['۷'],
	'8': ['۸'],
	'9': ['۹']
	}

	KASHMIRI_ENG_DIGITS_MAP: Dict = {
	'۰': ['0'],
	'۱': ['1'],
	'۲': ['2'],
	'۳': ['3'],
	'۴': ['4'],
	'۵': ['5'],
	'۶': ['6'],
	'۷': ['7'],
	'۸': ['8'],
	'۹': ['9']
	}
	KASHMIRI_DIACRITICS: FrozenSet[str] = frozenset("\u064e \u0670 \u0654 \u0650 \u0656 \u0655 \u065f \u064f \u0657 \u065A \u065b".split())

	KASHMIRI_PUNCTUATIONS: FrozenSet[str] = frozenset("؛ ، ٫ ؟ ۔ ٪".split())

	# Characters, Diacritics, Digits (Both sets), and Punctuations suitable for TTS vocabulary
	ALL_CHARACTERS: FrozenSet[str] = frozenset(
	list(KASHMIRI_CHARACTER_MAPPING.keys()) +
	list(KASHMIRI_DIACRITICS) +
	list(KASHMIRI_PUNCTUATIONS) +
	list(ENG_KASHMIRI_DIGITS_MAP.keys()) +
	list(PUNCTUATION_MAP.keys())
	)

	WORD_TO_DIGIT_MAP: Dict[str, List[str]] = {
	'صفرٕ': ['0'],
	'اکھ': ['1'],
	'زٕ': ['2'],
	'ترٛےٚ': ['3'],
	'ژور': ['4'],
	'پانژھ': ['5'],
	'شیٚیہ': ['6'],
	'ستھ': ['7'],
	'ٲٹھ': ['8'],
	'نو': ['9']
	}