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Add --use_fast option (closes #3741)

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oobabooga 2023-09-25 12:19:43 -07:00
parent b973b91d73
commit d0d221df49
6 changed files with 22 additions and 13 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:
| `--xformers` | Use xformer's memory efficient attention. This should increase your tokens/s. |
| `--sdp-attention` | Use torch 2.0's sdp attention. |
| `--trust-remote-code` | Set trust_remote_code=True while loading a model. Necessary for ChatGLM and Falcon. |
| `--use_fast` | Set use_fast=True while loading a tokenizer. |
#### Accelerate 4-bit

6
modules/loaders.py
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@ -20,6 +20,7 @@ loaders_and_params = OrderedDict({
'quant_type',
'compute_dtype',
'trust_remote_code',
'use_fast',
'alpha_value',
'rope_freq_base',
'compress_pos_emb',
@ -33,6 +34,7 @@ loaders_and_params = OrderedDict({
'rope_freq_base',
'compress_pos_emb',
'cfg_cache',
'use_fast',
'exllama_HF_info',
],
'ExLlamav2_HF': [
@ -41,6 +43,7 @@ loaders_and_params = OrderedDict({
'cfg_cache',
'alpha_value',
'compress_pos_emb',
'use_fast',
],
'ExLlama': [
'gpu_split',
@ -71,6 +74,7 @@ loaders_and_params = OrderedDict({
'disk',
'auto_devices',
'trust_remote_code',
'use_fast',
'autogptq_info',
],
'GPTQ-for-LLaMa': [
@ -78,6 +82,7 @@ loaders_and_params = OrderedDict({
'groupsize',
'model_type',
'pre_layer',
'use_fast',
'gptq_for_llama_info',
],
'llama.cpp': [
@ -111,6 +116,7 @@ loaders_and_params = OrderedDict({
'compress_pos_emb',
'cpu',
'cfg_cache',
'use_fast',
'llamacpp_HF_info',
],
'ctransformers': [

25
modules/models.py
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@ -99,18 +99,14 @@ def load_tokenizer(model_name, model):
if any(s in model_name.lower() for s in ['gpt-4chan', 'gpt4chan']) and Path(f"{shared.args.model_dir}/gpt-j-6B/").exists():
tokenizer = AutoTokenizer.from_pretrained(Path(f"{shared.args.model_dir}/gpt-j-6B/"))
elif path_to_model.exists():
try:
tokenizer = AutoTokenizer.from_pretrained(
path_to_model,
trust_remote_code=shared.args.trust_remote_code,
use_fast=False
)
except ValueError:
tokenizer = AutoTokenizer.from_pretrained(
path_to_model,
trust_remote_code=shared.args.trust_remote_code,
use_fast=True
)
if shared.args.use_fast:
logger.info('Loading the tokenizer with use_fast=True.')
tokenizer = AutoTokenizer.from_pretrained(
path_to_model,
trust_remote_code=shared.args.trust_remote_code,
use_fast=shared.args.use_fast
)
return tokenizer
@ -249,10 +245,13 @@ def llamacpp_HF_loader(model_name):
logger.error("Could not load the model because a tokenizer in transformers format was not found. Please download oobabooga/llama-tokenizer.")
return None, None
if shared.args.use_fast:
logger.info('Loading the tokenizer with use_fast=True.')
tokenizer = AutoTokenizer.from_pretrained(
path,
trust_remote_code=shared.args.trust_remote_code,
use_fast=False
use_fast=shared.args.use_fast
)
model = LlamacppHF.from_pretrained(model_name)

1
modules/shared.py
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@ -105,6 +105,7 @@ parser.add_argument('--no-cache', action='store_true', help='Set use_cache to Fa
parser.add_argument('--xformers', action='store_true', help="Use xformer's memory efficient attention. This should increase your tokens/s.")
parser.add_argument('--sdp-attention', action='store_true', help="Use torch 2.0's sdp attention.")
parser.add_argument('--trust-remote-code', action='store_true', help="Set trust_remote_code=True while loading a model. Necessary for ChatGLM and Falcon.")
parser.add_argument('--use_fast', action='store_true', help="Set use_fast=True while loading a tokenizer.")
# Accelerate 4-bit
parser.add_argument('--load-in-4bit', action='store_true', help='Load the model with 4-bit precision (using bitsandbytes).')

1
modules/ui.py
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@ -52,6 +52,7 @@ def list_model_elements():
'bf16',
'load_in_8bit',
'trust_remote_code',
'use_fast',
'load_in_4bit',
'compute_dtype',
'quant_type',

1
modules/ui_model_menu.py
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@ -115,6 +115,7 @@ def create_ui():
shared.gradio['tensor_split'] = gr.Textbox(label='tensor_split', info='Split the model across multiple GPUs, comma-separated list of proportions, e.g. 18,17')
shared.gradio['llama_cpp_seed'] = gr.Number(label='Seed (0 for random)', value=shared.args.llama_cpp_seed)
shared.gradio['trust_remote_code'] = gr.Checkbox(label="trust-remote-code", value=shared.args.trust_remote_code, info='Make sure to inspect the .py files inside the model folder before loading it with this option enabled.')
shared.gradio['use_fast'] = gr.Checkbox(label="use_fast", value=shared.args.use_fast, info='Set use_fast=True while loading the tokenizer. May trigger a conversion that takes several minutes.')
shared.gradio['disable_exllama'] = gr.Checkbox(label="disable_exllama", value=shared.args.disable_exllama, info='Disable ExLlama kernel.')
shared.gradio['gptq_for_llama_info'] = gr.Markdown('GPTQ-for-LLaMa support is currently only kept for compatibility with older GPUs. AutoGPTQ or ExLlama is preferred when compatible. GPTQ-for-LLaMa is installed by default with the webui on supported systems. Otherwise, it has to be installed manually following the instructions here: [instructions](https://github.com/oobabooga/text-generation-webui/blob/main/docs/GPTQ-models-(4-bit-mode).md#installation-1).')
shared.gradio['exllama_info'] = gr.Markdown('For more information, consult the [docs](https://github.com/oobabooga/text-generation-webui/blob/main/docs/ExLlama.md).')