tiny-random-LlamaForCausalLM-ONNX

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Model Details

Code to generate

import torch
from transformers import LlamaForCausalLM, LlamaConfig, AutoTokenizer

# Set seed for reproducibility
torch.manual_seed(0)

# Initializing the configuration
configuration = LlamaConfig(
  head_dim=16,
  hidden_size=32,
  intermediate_size=64,
  max_position_embeddings=131072,
  model_type="llama",
  num_attention_heads=2,
  num_hidden_layers=1,
  num_key_value_heads=2,
  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,
  vocab_size=128256,
)

# Initializing a model from the configuration
model = LlamaForCausalLM(configuration)

# Re-use tokenizer
tokenizer = AutoTokenizer.from_pretrained("Xenova/Llama-3.2-Tokenizer")

# Upload to the HF Hub
model_id = 'onnx-community/tiny-random-LlamaForCausalLM-ONNX'
model.push_to_hub(model_id)
tokenizer.push_to_hub(model_id)

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