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---
language: en
license: other
tags:
- meta
- GPTQ
- facebook
- llama
- llama2
base_model: meta-llama/Llama-2-7b-hf
model_name: Llama-2-7b-hf-AutoGPTQ
library:
- Transformers
- GPTQ
model_type: llama
pipeline_tag: text-generation
qunatized_by: twhoool02
---
# Model Card for LlamaForCausalLM(
(model): LlamaModel(
(embed_tokens): Embedding(32000, 4096)
(layers): ModuleList(
(0-31): 32 x LlamaDecoderLayer(
(self_attn): LlamaSdpaAttention(
(rotary_emb): LlamaRotaryEmbedding()
(k_proj): QuantLinear()
(o_proj): QuantLinear()
(q_proj): QuantLinear()
(v_proj): QuantLinear()
)
(mlp): LlamaMLP(
(act_fn): SiLU()
(down_proj): QuantLinear()
(gate_proj): QuantLinear()
(up_proj): QuantLinear()
)
(input_layernorm): LlamaRMSNorm()
(post_attention_layernorm): LlamaRMSNorm()
)
)
(norm): LlamaRMSNorm()
)
(lm_head): Linear(in_features=4096, out_features=32000, bias=False)
)
## Model Details
This model is a GPTQ quantized version of the meta-llama/Llama-2-7b-hf model.
- **Developed by:** Ted Whooley
- **Library:** Transformers, GPTQ
- **Model type:** llama
- **Model name:** LlamaForCausalLM(
(model): LlamaModel(
(embed_tokens): Embedding(32000, 4096)
(layers): ModuleList(
(0-31): 32 x LlamaDecoderLayer(
(self_attn): LlamaSdpaAttention(
(rotary_emb): LlamaRotaryEmbedding()
(k_proj): QuantLinear()
(o_proj): QuantLinear()
(q_proj): QuantLinear()
(v_proj): QuantLinear()
)
(mlp): LlamaMLP(
(act_fn): SiLU()
(down_proj): QuantLinear()
(gate_proj): QuantLinear()
(up_proj): QuantLinear()
)
(input_layernorm): LlamaRMSNorm()
(post_attention_layernorm): LlamaRMSNorm()
)
)
(norm): LlamaRMSNorm()
)
(lm_head): Linear(in_features=4096, out_features=32000, bias=False)
)
- **Pipeline tag:** text-generation
- **Qunatized by:** twhoool02
- **Language(s) (NLP):** en
- **License:** other
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