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LlamaForCausalLM (Standard MHA)float32 / float16| Data Source | Approx. Size | Primary Focus | Link |
|---|---|---|---|
| BILGEM AI Synthetic Web | ~2.0 GB | General Web, Knowledge & Grammar | BILGEM-AI/BILGE-Synthetic-Web |
| BILGEM AI Synthetic Math | ~750 MB | Mathematical Reasoning & Logic | BILGEM-AI/BILGE-Synthetic-Math |
| BILGEM AI Synthetic Stories | ~750 MB | Narrative Flow & Text Generation | BILGEM-AI/BILGE-Synthetic-Stories |
1import torch
2from transformers import AutoModelForCausalLM, AutoTokenizer
3
4model_id = "AhıskaAI/AhıskaAI-110M-Experimental-v0.1"
5
6tokenizer = AutoTokenizer.from_pretrained(model_id)
7model = AutoModelForCausalLM.from_pretrained(
8 model_id,
9 torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
10 device_map="auto"
11)
12
13prompt = "Bir zamanlar uzak bir ülkede"
14inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
15
16outputs = model.generate(
17 **inputs,
18 max_new_tokens=100,
19 temperature=0.7,
20 top_p=0.9,
21 do_sample=True
22)
23
24print(tokenizer.decode(outputs[0], skip_special_tokens=True))