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Cornell-RelaxML / quip-sharp

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Llama-2-7b-E8P-2Bit not loading correctly. #39

Closed YilunKuang closed 9 months ago

YilunKuang commented 9 months ago

Hi,

I was loading this model https://huggingface.co/relaxml/Llama-2-7b-E8P-2Bit from huggingface. 

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("relaxml/Llama-2-7b-E8P-2Bit")
model = AutoModelForCausalLM.from_pretrained("relaxml/Llama-2-7b-E8P-2Bit")

It gives an error message about model loading:

Some weights of the model checkpoint at relaxml/Llama-2-7b-E8P-2Bit were not used when initializing LlamaForCausalLM: ['model.layers.27.self_attn.qkv_proj.codebook_id', 'model.layers.19.mlp.down_proj.Qidxs', 'model.layers.26.self_attn.qkv_proj.codebook_id', 'model.layers.15.self_attn.qkv_proj.SV', 'model.layers.16.self_attn.o_proj.Wscale', 'model.layers.23.mlp.down_proj.SU', 'model.layers.8.mlp.upgate_proj.SU', 'model.layers.6.self_attn.qkv_proj.Qidxs', 'model.layers.24.self_attn.o_proj.SU', 'model.layers.17.mlp.upgate_proj.SU', 'model.layers.23.self_attn.o_proj.SU', 'model.layers.9.mlp.down_proj.SU', 'model.layers.24.mlp.down_proj.codebook_id', 'model.layers.28.self_attn.o_proj.Qidxs', 'model.layers.2.self_attn.o_proj.codebook_id', 'model.layers.26.self_attn.o_proj.Qidxs', 'model.layers.10.mlp.down_proj.SV', 'model.layers.25.self_attn.o_proj.SU', 'model.layers.2.mlp.upgate_proj.fuse_scales', 'model.layers.21.mlp.upgate_proj.codebook_id', 'model.layers.31.self_attn.o_proj.codebook_id', 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- This IS expected if you are initializing LlamaForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing LlamaForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
Some weights of LlamaForCausalLM were not initialized from the model checkpoint at relaxml/Llama-2-7b-E8P-2Bit and are newly initialized: ['model.layers.15.self_attn.q_proj.weight', 'model.layers.24.mlp.down_proj.weight', 'model.layers.20.self_attn.v_proj.weight', 'model.layers.16.mlp.up_proj.weight', 'model.layers.21.mlp.gate_proj.weight', 'model.layers.18.self_attn.q_proj.weight', 'model.layers.3.mlp.up_proj.weight', 'model.layers.22.self_attn.o_proj.weight', 'model.layers.17.mlp.up_proj.weight', 'model.layers.26.self_attn.o_proj.weight', 'model.layers.26.mlp.gate_proj.weight', 'model.layers.23.self_attn.v_proj.weight', 'model.layers.2.self_attn.q_proj.weight', 'model.layers.21.mlp.down_proj.weight', 'model.layers.3.self_attn.o_proj.weight', 'model.layers.4.mlp.up_proj.weight', 'model.layers.5.self_attn.k_proj.weight', 'model.layers.16.self_attn.q_proj.weight', 'model.layers.20.self_attn.o_proj.weight', 'model.layers.15.mlp.up_proj.weight', 'model.layers.2.mlp.gate_proj.weight', 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You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.

I tested this model by doing some text generation:

(Pdb) model.generate(max_length=30)
tensor([[    1, 24279, 31730, 24945,  7771, 17308, 17698, 23431, 29339, 31895,
         10582, 21101, 31730, 21554, 17698, 23431, 17698, 11814, 21727, 21727,
         31730, 23431,  8950, 17698, 31730, 17698, 21727, 22823, 10582, 23431]],
       device='cuda:0')
(Pdb) generated_id = self.model.generate(max_length=30)
(Pdb) tokenizer.batch_decode(generated_id, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
'Bedeutovystru Bayer Browagi scales식reraagicolon scales식ksam富富agirebmathchar富ozzárefix scalesmathchar Bayer scales scales Bedeutksam'

It seems like this checkpoint is not loaded properly, otherwise there should be better generated text.

YilunKuang commented 9 months ago

fixed it by using interactive_gen.py. marking this as closed.