What is it?

This is a quantized version of h2oai/h2ogpt-4096-llama2-13b-chat, formatted in GGUF format to be run with llama.cpp and similar inference tools. The convert.py script from llama.cpp was used for the conversion.

Available Formats

Format	Bits	Use case
q8_0	8	Original quant method, 8-bit.

Original Model Card

h2oGPT clone of Meta's Llama 2 13B Chat.

Try it live on our h2oGPT demo with side-by-side LLM comparisons and private document chat!

See how it compares to other models on our LLM Leaderboard!

See more at H2O.ai

Model Architecture

LlamaForCausalLM(
  (model): LlamaModel(
    (embed_tokens): Embedding(32000, 5120, padding_idx=0)
    (layers): ModuleList(
      (0-39): 40 x LlamaDecoderLayer(
        (self_attn): LlamaAttention(
          (q_proj): Linear(in_features=5120, out_features=5120, bias=False)
          (k_proj): Linear(in_features=5120, out_features=5120, bias=False)
          (v_proj): Linear(in_features=5120, out_features=5120, bias=False)
          (o_proj): Linear(in_features=5120, out_features=5120, bias=False)
          (rotary_emb): LlamaRotaryEmbedding()
        )
        (mlp): LlamaMLP(
          (gate_proj): Linear(in_features=5120, out_features=13824, bias=False)
          (up_proj): Linear(in_features=5120, out_features=13824, bias=False)
          (down_proj): Linear(in_features=13824, out_features=5120, bias=False)
          (act_fn): SiLUActivation()
        )
        (input_layernorm): LlamaRMSNorm()
        (post_attention_layernorm): LlamaRMSNorm()
      )
    )
    (norm): LlamaRMSNorm()
  )
  (lm_head): Linear(in_features=5120, out_features=32000, bias=False)
)