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SupraLabs
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SupraLabs
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Supra2.1-Ultra is the model that refers to the Supra2.1 family. It has 230M params, 40B tokens trained on, with LLaMa arch. It is a small base model that is probably going to generate incorrect or biased text, and it has neither been aligned nor evaluated for safety.
| Spec | Details |
|---|---|
| Parameters | 230M |
| Tokens seen | ~40.4B |
| Arch | Llama |
| Layers | 32 |
| Hidden size | 768 |
| Intermediate size (MLP) | 1920 |
| Attention heads | 12 (head dim 64) |
| KV heads (GQA) | 4 |
| Vocabulary size | 49,152 |
| Context length | 2,048 |
| RoPE theta | 10,000 |
| Activation | SiLU (SwiGLU MLP) |
| Tied embeddings | Yes |
| Precision | bfloat16 |
HuggingFaceFW/fineweb-edu
mlfoundations/dclm-baseline-1.0
HuggingFaceTB/finemath
This model was trained on a single A100 SXM.
| Benchmark | Shots | acc | acc_norm | Random |
|---|---|---|---|---|
| HellaSwag | 0 | 31.64 | 37.18 | 25.0 |
| PIQA | 0 | 65.78 | 64.91 | 50.0 |
| ARC-Easy | 0 | 57.11 | 50.46 | 25.0 |
python
import torchfrom transformers import AutoModelForCausalLM, AutoTokenizer model_id = "SupraLabs/Supra2.1-Ultra" tokenizer = AutoTokenizer.from_pretrained(model_id)model = AutoModelForCausalLM.from_pretrained(model_id, dtype=torch.bfloat16) prompt = "The capital of France is"inputs = tokenizer(prompt, return_tensors="pt") output = model.generate( **inputs, max_new_tokens=50, do_sample=True, temperature=0.7, top_p=0.9, pad_token_id=tokenizer.eos_token_id,)print(tokenizer.decode(output[0], skip_special_tokens=True))This code should download the model and generate a response.
This model is released under Apache-2.0 License.
thanks to:
Dedeprogames, for code to train this model.
SupraLabs Org © - 2026
| ARC-Challenge | 0 | 25.00 | 26.28 | 25.0 |
| Arithmark-v3 | 0 | 38.00 | 38.20 | - |
| Open SLM leaderboard's II | - | 20.64 | - | - |