Update README.md

README.md

@@ -1,52 +1,53 @@
----
-license: apache-2.0
-datasets:
-- google/docci
-- google/imageinwords
-- ProGamerGov/synthetic-dataset-1m-dalle3-high-quality-captions
-language:
-- en
-library_name: transformers
-pipeline_tag: image-text-to-text
-tags:
-- art
-inference: false
----
-
-Original model is [here](https://huggingface.co/gokaygokay/Florence-2-SD3-Captioner).
-Tagger for local environment is [here](https://huggingface.co/John6666/local_gokaygokay_Florence-2-SD3-Captioner_Tagger).
-
-```python
-# recipe
-from transformers import AutoModelForCausalLM, AutoProcessor, BitsAndBytesConfig
-import transformers
-import torch
-import json
-
-model_id = 'gokaygokay/Florence-2-SD3-Captioner'
-save_path = 'gokaygokay-Florence-2-SD3-Captioner-8bit'
-
-processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained(
-    model_id, 
-    trust_remote_code=True,
-    torch_dtype=torch.float32,
-    low_cpu_mem_usage=True,
-    quantization_config=BitsAndBytesConfig(
-        load_in_8bit=True,
-        llm_int8_threshold=6.0,
-        llm_int8_enable_fp32_cpu_offload=True,
-        llm_int8_skip_modules=['lm_head'],
-    ),
-)
-
-processor.save_pretrained(save_path)
-model.save_pretrained(save_path, safe_serialization=True)
-
-config = {}
-with open(f'{save_path}/config.json') as f:
-    config = json.load(f)
-config['vision_config']['model_type'] = 'davit'
-with open(f'{save_path}/config.json', 'w') as f:
-    json.dump(config, f, indent=2)
+---
+license: apache-2.0
+datasets:
+- google/docci
+- google/imageinwords
+- ProGamerGov/synthetic-dataset-1m-dalle3-high-quality-captions
+language:
+- en
+library_name: transformers
+pipeline_tag: image-text-to-text
+tags:
+- art
+base_model: gokaygokay/Florence-2-SD3-Captioner
+inference: false
+---
+
+Original model is [here](https://huggingface.co/gokaygokay/Florence-2-SD3-Captioner).
+Tagger for local environment is [here](https://huggingface.co/John6666/local_gokaygokay_Florence-2-SD3-Captioner_Tagger).
+
+```python
+# recipe
+from transformers import AutoModelForCausalLM, AutoProcessor, BitsAndBytesConfig
+import transformers
+import torch
+import json
+
+model_id = 'gokaygokay/Florence-2-SD3-Captioner'
+save_path = 'gokaygokay-Florence-2-SD3-Captioner-8bit'
+
+processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id, 
+    trust_remote_code=True,
+    torch_dtype=torch.float32,
+    low_cpu_mem_usage=True,
+    quantization_config=BitsAndBytesConfig(
+        load_in_8bit=True,
+        llm_int8_threshold=6.0,
+        llm_int8_enable_fp32_cpu_offload=True,
+        llm_int8_skip_modules=['lm_head'],
+    ),
+)
+
+processor.save_pretrained(save_path)
+model.save_pretrained(save_path, safe_serialization=True)
+
+config = {}
+with open(f'{save_path}/config.json') as f:
+    config = json.load(f)
+config['vision_config']['model_type'] = 'davit'
+with open(f'{save_path}/config.json', 'w') as f:
+    json.dump(config, f, indent=2)
 ```