optimum-neuron-cache
/
neuronxcc-2.15.128.0+56dc5a86
/0_REGISTRY
/0.0.25.dev0
/training
/llama
/meta-llama
/Llama-3.2-1B
/0ea58707c15b63f1d3f9.json
{"architectures": ["LlamaForCausalLM"], "attention_bias": false, "attention_dropout": 0.0, "bos_token_id": 128256, "eos_token_id": 128257, "head_dim": 64, "hidden_act": "silu", "hidden_size": 2048, "initializer_range": 0.02, "intermediate_size": 8192, "max_position_embeddings": 131072, "mlp_bias": false, "model_type": "llama", "neuron": {"compiler_version": "2.15.128.0+56dc5a86", "input_specs": {"chosen": ["<|im_start|>user\nLet $r=3^s-s$ and $s=2^n+1$. What is the value of $r$ when $n=2$?<|im_end|>\n<|im_start|>assistant\nTo find the value of $r$ when $n=2$, I need to first plug in $n=2$ into the expression for $s$ and simplify.\nThat gives me $s=2^2+1=4+1=5$.\nNow that I have $s=5$, I can plug that into the expression for $r$ and simplify again.\nThat gives me $r=3^5-5=243-5=238$.\nSo the value of $r$ when $n=2$ is $238$.\n\n# Answer\n\n238<|im_end|>\n"], "chosen_attention_mask": [1, 512], "chosen_input_ids": [1, 512], "chosen_labels": [1, 512], "prompt": ["Let $r=3^s-s$ and $s=2^n+1$. What is the value of $r$ when $n=2$?"], "prompt_attention_mask": [1, 512], "prompt_input_ids": [1, 512], "question": ["Let $r=3^s-s$ and $s=2^n+1$. What is the value of $r$ when $n=2$?"], "rejected": ["<|im_start|>user\nLet $r=3^s-s$ and $s=2^n+1$. What is the value of $r$ when $n=2$?<|im_end|>\n<|im_start|>assistant\nFirst substitute $n=2$ into the expression for $s$ to find $s=2^2+1=5$. Then substitute $s=5$ into the expression for $r$ to find $r=3^5-5=243-5=\\boxed{238}$.<|im_end|>\n"], "rejected_attention_mask": [1, 512], "rejected_input_ids": [1, 512], "rejected_labels": [1, 512], "source": ["prm_dpo_pairs"]}, "model_class": "PeftModelForCausalLM", "num_neuron_cores_per_node": 2, "pipeline_parallel_size": 1, "precision": "bfloat16", "tensor_parallel_size": 1, "training": true}, "num_attention_heads": 32, "num_hidden_layers": 16, "num_key_value_heads": 8, "pad_token_id": 128257, "pretraining_tp": 1, "rms_norm_eps": 1e-05, "rope_scaling": {"factor": 32.0, "high_freq_factor": 4.0, "low_freq_factor": 1.0, "original_max_position_embeddings": 8192, "rope_type": "llama3"}, "rope_theta": 500000.0, "tie_word_embeddings": true, "torch_dtype": "bfloat16", "use_cache": true, "vocab_size": 128258} |