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admijgjtjtjtjjg
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Model Details
Model Provider
admijgjtjtjtjjg
Model Tree
SupraLabs/Supra-50M-Reasoning
Input Modalities
Output Modalities
Supported Functionality
| Language | Script | Quality |
|---|---|---|
| ES, EN, DE | Latin | ✅ Excellent |
| FR, IT, PT, NL | Latin | ✅ Good |
| PL, CS, RO, HU | Latin | ✅ Functional |
| RU, EL | Cyrillic/Greek | ⚠️ Developing |
| ZH, JA, KO | CJK | ⚠️ Developing |
| AR, HE, HI, TH | Others | ⚠️ Emerging |
`python from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained('admijgjtjtjtjjg/supra-50m-multilingual') tokenizer = AutoTokenizer.from_pretrained('admijgjtjtjtjjg/supra-50m-multilingual')
prompt = 'Q: What is the capital of France?' inputs = tokenizer(prompt, return_tensors='pt') outputs = model.generate(**inputs, max_new_tokens=50) print(tokenizer.decode(outputs[0])) `
Or use with PEFT (LoRA adapter):
text
python from peft import PeftModel base = AutoModelForCausalLM.from_pretrained('SupraLabs/Supra-50M-Reasoning') model = PeftModel.from_pretrained(base, 'admijgjtjtjtjjg/supra-50m-multilingual')