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--- |
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license: mit |
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language: |
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- ru |
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library_name: transformers |
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--- |
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# llama-600M-rus |
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Simple amateur experimental model trained on approximately 60 Mb of text books from beginner in LLMs. |
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No resources and time to collect bigger dataset. |
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It could generate amateur, but no or less adequate output as well (in respect of training tokens)/ |
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The work can be used as a checkpoint for the further training or for experiments. |
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Simle usage example: |
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```python |
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from transformers import LlamaTokenizerFast, LlamaForCausalLM |
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model = LlamaForCausalLM.from_pretrained('demetera/llama-600M-rus') |
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tokenizer = LlamaTokenizerFast.from_pretrained('demetera/llama-600M-rus') |
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prompt = "Я вышел и улицу и" |
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inputs = tokenizer(prompt, return_tensors='pt') |
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outputs = model.generate(inputs.input_ids, attention_mask = inputs.attention_mask, max_new_tokens=250, do_sample=True, top_k=50, top_p=0.95) |
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print (tokenizer.decode(outputs[0], skip_special_tokens=True)) |
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``` |
