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  - lxcorp
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  ---
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- # lambdAI — Lightweight Math & Logic Reasoning Model
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- **lambdAI** is a compact, fine-tuned language model built on top of `TinyLlama-1.1B-Chat-v1.0`, designed for educational reasoning tasks in both Portuguese and English. It focuses on logic, number theory, and mathematics, delivering fast performance with minimal computational requirements.
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  ---
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  ```python
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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- model = AutoModelForCausalLM.from_pretrained("lxcorp/lambdai")
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- tokenizer = AutoTokenizer.from_pretrained("lxcorp/lambdai")
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  input_text = "Problema: Prove que 17 é um número primo."
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  inputs = tokenizer(input_text, return_tensors="pt")
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  output = model.generate(**inputs, max_new_tokens=100)
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  print(tokenizer.decode(output[0], skip_special_tokens=True))
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-
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  ---
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  About λχ Corp.
 
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  - lxcorp
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  ---
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+ # lambda-1v-1b — Lightweight Math & Logic Reasoning Model
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+ **lambda-1v-1b** is a compact, fine-tuned language model built on top of `TinyLlama-1.1B-Chat-v1.0`, designed for educational reasoning tasks in both Portuguese and English. It focuses on logic, number theory, and mathematics, delivering fast performance with minimal computational requirements.
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  ---
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  ```python
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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+ model = AutoModelForCausalLM.from_pretrained("lxcorp/lambda-1v-1b")
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+ tokenizer = AutoTokenizer.from_pretrained("lxcorp/lambda-1v-1b")
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  input_text = "Problema: Prove que 17 é um número primo."
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  inputs = tokenizer(input_text, return_tensors="pt")
 
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  output = model.generate(**inputs, max_new_tokens=100)
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  print(tokenizer.decode(output[0], skip_special_tokens=True))
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+ ```
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  ---
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  About λχ Corp.