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--- |
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license: llama2 |
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--- |
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# What is it? |
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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. |
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## Available Formats |
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| Format | Bits | Use case | |
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| ---- | ---- | ----- | |
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| q8_0 | 8 | Original quant method, 8-bit. | |
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# Original Model Card |
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h2oGPT clone of [Meta's Llama 2 13B Chat](https://huggingface.co./meta-llama/Llama-2-13b-chat-hf). |
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Try it live on our [h2oGPT demo](https://gpt.h2o.ai) with side-by-side LLM comparisons and private document chat! |
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See how it compares to other models on our [LLM Leaderboard](https://evalgpt.ai/)! |
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See more at [H2O.ai](https://h2o.ai/) |
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## Model Architecture |
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``` |
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LlamaForCausalLM( |
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(model): LlamaModel( |
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(embed_tokens): Embedding(32000, 5120, padding_idx=0) |
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(layers): ModuleList( |
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(0-39): 40 x LlamaDecoderLayer( |
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(self_attn): LlamaAttention( |
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(q_proj): Linear(in_features=5120, out_features=5120, bias=False) |
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(k_proj): Linear(in_features=5120, out_features=5120, bias=False) |
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(v_proj): Linear(in_features=5120, out_features=5120, bias=False) |
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(o_proj): Linear(in_features=5120, out_features=5120, bias=False) |
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(rotary_emb): LlamaRotaryEmbedding() |
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) |
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(mlp): LlamaMLP( |
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(gate_proj): Linear(in_features=5120, out_features=13824, bias=False) |
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(up_proj): Linear(in_features=5120, out_features=13824, bias=False) |
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(down_proj): Linear(in_features=13824, out_features=5120, bias=False) |
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(act_fn): SiLUActivation() |
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) |
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(input_layernorm): LlamaRMSNorm() |
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(post_attention_layernorm): LlamaRMSNorm() |
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) |
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) |
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(norm): LlamaRMSNorm() |
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) |
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(lm_head): Linear(in_features=5120, out_features=32000, bias=False) |
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) |
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``` |
