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Add Support for Static NTK RoPE scaling for exllama/exllama_hf (#2955)

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Panchovix 2023-07-04 00:13:16 -04:00 committed by GitHub
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commit 10c8c197bf
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7 changed files with 18 additions and 2 deletions
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1
README.md
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@ -269,6 +269,7 @@ Optionally, you can use the following command-line flags:
|`--gpu-split` | Comma-separated list of VRAM (in GB) to use per GPU device for model layers, e.g. `20,7,7` |
|`--max_seq_len MAX_SEQ_LEN` | Maximum sequence length. |
|`--compress_pos_emb COMPRESS_POS_EMB` | Positional embeddings compression factor. Should typically be set to max_seq_len / 2048. |
|`--alpha_value ALPHA_VALUE` | Positional embeddings alpha factor for NTK RoPE scaling. Same as above. Use either this or compress_pos_emb, not both. `
#### GPTQ-for-LLaMa

6
modules/exllama.py
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@ -53,13 +53,17 @@ class ExllamaModel:
if shared.args.gpu_split:
config.set_auto_map(shared.args.gpu_split)
config.gpu_peer_fix = True
if shared.args.alpha_value:
config.alpha_value = shared.args.alpha_value
config.calculate_rotary_embedding_base()
if torch_version.hip:
config.rmsnorm_no_half2 = True
config.rope_no_half2 = True
config.matmul_no_half2 = True
config.silu_no_half2 = True
model = ExLlama(config)
tokenizer = ExLlamaTokenizer(str(tokenizer_model_path))
cache = ExLlamaCache(model)

5
modules/exllama_hf.py
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@ -97,6 +97,11 @@ class ExllamaHF(PreTrainedModel):
if shared.args.gpu_split:
config.set_auto_map(shared.args.gpu_split)
config.gpu_peer_fix = True
if shared.args.alpha_value:
config.alpha_value = shared.args.alpha_value
config.calculate_rotary_embedding_base()
if torch.version.hip:
config.rmsnorm_no_half2 = True
config.rope_no_half2 = True

2
modules/loaders.py
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@ -57,12 +57,14 @@ loaders_and_params = {
'gpu_split',
'max_seq_len',
'compress_pos_emb',
'alpha_value',
'exllama_info',
],
'ExLlama_HF' : [
'gpu_split',
'max_seq_len',
'compress_pos_emb',
'alpha_value',
'exllama_HF_info',
]
}

1
modules/shared.py
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@ -150,6 +150,7 @@ parser.add_argument('--desc_act', action='store_true', help='For models that don
parser.add_argument('--gpu-split', type=str, help="Comma-separated list of VRAM (in GB) to use per GPU device for model layers, e.g. 20,7,7")
parser.add_argument('--max_seq_len', type=int, default=2048, help="Maximum sequence length.")
parser.add_argument('--compress_pos_emb', type=int, default=1, help="Positional embeddings compression factor. Should typically be set to max_seq_len / 2048.")
parser.add_argument('--alpha_value', type=int, default=1, help="Positional embeddings alpha factor for NTK RoPE scaling. Same as above. Use either this or compress_pos_emb, not both.")
# FlexGen
parser.add_argument('--flexgen', action='store_true', help='DEPRECATED')

4
modules/ui.py
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@ -63,9 +63,11 @@ def list_model_elements():
'llama_cpp_seed',
'gpu_split',
'max_seq_len',
'compress_pos_emb'
'compress_pos_emb',
'alpha_value'
]
for i in range(torch.cuda.device_count()):
elements.append(f'gpu_memory_{i}')

1
server.py
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@ -226,6 +226,7 @@ def create_model_menus():
shared.gradio['gpu_split'] = gr.Textbox(label='gpu-split', info='Comma-separated list of VRAM (in GB) to use per GPU. Example: 20,7,7')
shared.gradio['max_seq_len'] = gr.Slider(label='max_seq_len', minimum=2048, maximum=16384, step=256, info='Maximum sequence length.', value=shared.args.max_seq_len)
shared.gradio['compress_pos_emb'] = gr.Slider(label='compress_pos_emb', minimum=1, maximum=8, step=1, info='Positional embeddings compression factor. Should typically be set to max_seq_len / 2048.', value=shared.args.compress_pos_emb)
shared.gradio['alpha_value'] = gr.Slider(label='alpha_value', minimum=1, maximum=8, step=1, info='Positional embeddings alpha factor for NTK RoPE scaling. Same as above. Use either this or compress_pos_emb, not both.', value=shared.args.alpha_value)
with gr.Column():
shared.gradio['triton'] = gr.Checkbox(label="triton", value=shared.args.triton)