Read more metadata (config.json & quantize_config.json)

models/config.yaml

@@ -6,8 +6,6 @@
   model_type: 'gptj'
 .*(gpt-neox|koalpaca-polyglot|polyglot.*koalpaca|polyglot-ko|polyglot_ko|pythia|stablelm|incite|dolly-v2|polycoder|h2ogpt-oig|h2ogpt-oasst1|h2ogpt-gm):
   model_type: 'gptneox'
-.*llama:
-  model_type: 'llama'
 .*bloom:
   model_type: 'bloom'
 .*gpt2:
@@ -22,38 +20,32 @@
   model_type: 'dollyv2'
 .*replit:
   model_type: 'replit'
-llama-65b-gptq-3bit:
-  groupsize: 'None'
-.*(4bit|int4):
-  wbits: 4
-.*(3bit|int3):
-  wbits: 3
-.*(-2bit|_2bit|int2-):
-  wbits: 2
-.*(-1bit|_1bit|int1-):
-  wbits: 1
-.*(8bit|int8):
-  wbits: 8
-.*(-7bit|_7bit|int7-):
-  wbits: 7
-.*(-6bit|_6bit|int6-):
-  wbits: 6
-.*(-5bit|_5bit|int5-):
-  wbits: 5
-.*(-gr32-|-32g-|groupsize32|-32g$):
-  groupsize: 32
-.*(-gr64-|-64g-|groupsize64|-64g$):
-  groupsize: 64
-.*(gr128|128g|groupsize128):
-  groupsize: 128
-.*(gr1024|1024g|groupsize1024):
-  groupsize: 1024
 .*(oasst|openassistant-|stablelm-7b-sft-v7-epoch-3):
   instruction_template: 'Open Assistant'
   skip_special_tokens: false
 (?!.*galactica)(?!.*reward).*openassistant:
   instruction_template: 'Open Assistant'
   skip_special_tokens: false
+.*galactica:
+  skip_special_tokens: false
+.*dolly-v[0-9]-[0-9]*b:
+  instruction_template: 'Alpaca'
+  skip_special_tokens: false
+.*alpaca-native-4bit:
+  instruction_template: 'Alpaca'
+  custom_stopping_strings: '"### End"'
+.*llava:
+  instruction_template: 'LLaVA'
+  custom_stopping_strings: '"\n###"'
+.*wizard.*mega:
+  instruction_template: 'Wizard-Mega'
+  custom_stopping_strings: '"</s>"'
+.*starchat-beta:
+  instruction_template: 'Starchat-Beta'
+  custom_stopping_strings: '"<|end|>"'
+.*(openorca-platypus2):
+  instruction_template: 'OpenOrca-Platypus2'
+  custom_stopping_strings: '"### Instruction:", "### Response:"'
 (?!.*v0)(?!.*1.1)(?!.*1_1)(?!.*stable)(?!.*chinese).*vicuna:
   instruction_template: 'Vicuna-v0'
 .*vicuna.*v0:
@@ -70,26 +62,12 @@ llama-65b-gptq-3bit:
   instruction_template: 'Chinese-Vicuna-Chat'
 .*alpaca:
   instruction_template: 'Alpaca'
-.*alpaca-native-4bit:
-  instruction_template: 'Alpaca'
-  wbits: 4
-  groupsize: 128
-.*galactica:
-  skip_special_tokens: false
-.*dolly-v[0-9]-[0-9]*b:
-  instruction_template: 'Alpaca'
-  skip_special_tokens: false
-  custom_stopping_strings: '"### End"'
 .*koala:
   instruction_template: 'Koala'
 .*chatglm:
   instruction_template: 'ChatGLM'
 .*(metharme|pygmalion|mythalion):
   instruction_template: 'Metharme'
-.*llava:
-  model_type: 'llama'
-  instruction_template: 'LLaVA'
-  custom_stopping_strings: '"\n###"'
 .*raven:
   instruction_template: 'RWKV-Raven'
 .*moss-moon.*sft:
@@ -116,9 +94,6 @@ llama-65b-gptq-3bit:
   instruction_template: 'INCITE-Chat'
 .*incite.*instruct:
   instruction_template: 'INCITE-Instruct'
-.*wizard.*mega:
-  instruction_template: 'Wizard-Mega'
-  custom_stopping_strings: '"</s>"'
 .*ziya-:
   instruction_template: 'Ziya'
 .*koalpaca:
@@ -169,14 +144,10 @@ llama-65b-gptq-3bit:
   instruction_template: 'Samantha'
 .*wizardcoder:
   instruction_template: 'Alpaca'
-.*starchat-beta:
-  instruction_template: 'Starchat-Beta'
-  custom_stopping_strings: '"<|end|>"'
 .*minotaur:
   instruction_template: 'Minotaur'
 .*orca_mini:
   instruction_template: 'Orca Mini'
-  instruction_template: 'Vicuna-v0'
 .*(platypus|gplatty|superplatty):
   instruction_template: 'Alpaca'
 .*longchat:
@@ -199,12 +170,6 @@ llama-65b-gptq-3bit:
   instruction_template: 'StableBeluga2'
 .*openchat:
   instruction_template: 'OpenChat'
-.*falcon.*-instruct:
-.*(openorca-platypus2):
-  instruction_template: 'OpenOrca-Platypus2'
-  custom_stopping_strings: '"### Instruction:", "### Response:"'
-.*codellama:
-  rope_freq_base: 1000000
 .*codellama.*instruct:
   instruction_template: 'Llama-v2'
 .*mistral.*instruct:

modules/models_settings.py

@@ -10,16 +10,16 @@ from modules import loaders, metadata_gguf, shared, ui
 def get_fallback_settings():
     return {
         'wbits': 'None',
-        'model_type': 'None',
         'groupsize': 'None',
-        'pre_layer': 0,
-        'skip_special_tokens': shared.settings['skip_special_tokens'],
-        'custom_stopping_strings': shared.settings['custom_stopping_strings'],
-        'truncation_length': shared.settings['truncation_length'],
+        'desc_act': False,
+        'model_type': 'None',
         'max_seq_len': 2048,
         'n_ctx': 2048,
         'rope_freq_base': 0,
         'compress_pos_emb': 1,
+        'truncation_length': shared.settings['truncation_length'],
+        'skip_special_tokens': shared.settings['skip_special_tokens'],
+        'custom_stopping_strings': shared.settings['custom_stopping_strings'],
     }
 
 
@@ -56,8 +56,8 @@ def get_model_metadata(model):
         if 'llama.rope.freq_base' in metadata:
             model_settings['rope_freq_base'] = metadata['llama.rope.freq_base']
 
-    # Read transformers metadata. In particular, the sequence length for the model.
     else:
+        # Read transformers metadata
         path = Path(f'{shared.args.model_dir}/{model}/config.json')
         if path.exists():
             metadata = json.loads(open(path, 'r').read())
@@ -65,6 +65,32 @@ def get_model_metadata(model):
                 model_settings['truncation_length'] = metadata['max_position_embeddings']
                 model_settings['max_seq_len'] = metadata['max_position_embeddings']
 
+            if 'rope_theta' in metadata:
+                model_settings['rope_freq_base'] = metadata['rope_theta']
+
+            if 'rope_scaling' in metadata and type(metadata['rope_scaling']) is dict and all(key in metadata['rope_scaling'] for key in ('type', 'factor')):
+                if metadata['rope_scaling']['type'] == 'linear':
+                    model_settings['compress_pos_emb'] = metadata['rope_scaling']['factor']
+
+            if 'quantization_config' in metadata:
+                if 'bits' in metadata['quantization_config']:
+                    model_settings['wbits'] = metadata['quantization_config']['bits']
+                if 'group_size' in metadata['quantization_config']:
+                    model_settings['groupsize'] = metadata['quantization_config']['group_size']
+                if 'desc_act' in metadata['quantization_config']:
+                    model_settings['desc_act'] = metadata['quantization_config']['desc_act']
+
+        # Read AutoGPTQ metadata
+        path = Path(f'{shared.args.model_dir}/{model}/quantize_config.json')
+        if path.exists():
+            metadata = json.loads(open(path, 'r').read())
+            if 'bits' in metadata:
+                model_settings['wbits'] = metadata['bits']
+            if 'group_size' in metadata:
+                model_settings['groupsize'] = metadata['group_size']
+            if 'desc_act' in metadata:
+                model_settings['desc_act'] = metadata['desc_act']
+
     # Apply user settings from models/config-user.yaml
     settings = shared.user_config
     for pat in settings:

modules/ui_model_menu.py

@@ -258,9 +258,10 @@ def download_model_wrapper(repo_id, specific_file, progress=gr.Progress(), retur
 
 
 def update_truncation_length(current_length, state):
-    if state['loader'].lower().startswith('exllama'):
-        return state['max_seq_len']
-    elif state['loader'] in ['llama.cpp', 'llamacpp_HF', 'ctransformers']:
-        return state['n_ctx']
-    else:
-        return current_length
+    if 'loader' in state:
+        if state['loader'].lower().startswith('exllama'):
+            return state['max_seq_len']
+        elif state['loader'] in ['llama.cpp', 'llamacpp_HF', 'ctransformers']:
+            return state['n_ctx']
+
+    return current_length