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NaughtyDog97
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DFE-GPS-9B

Text Generation
Transformers
Safetensors
fegeo-llama
conversational
custom_code
Model card Files
xet
Community
zezeze97 commited on
Commit
42e4305
·
1 Parent(s): cd994b0

update

Browse files
Files changed (7) hide show
  1. .DS_Store +0 -0
  2. README.md +5 -5
  3. config.json +1 -1
  4. model-00001-of-00004.safetensors +1 -1
  5. model-00002-of-00004.safetensors +1 -1
  6. model-00003-of-00004.safetensors +1 -1
  7. model-00004-of-00004.safetensors +1 -1
.DS_Store ADDED
Binary file (6.15 kB). View file
 
README.md CHANGED
@@ -30,12 +30,12 @@ torch.set_default_device(device)
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  # create model
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  model = AutoModelForCausalLM.from_pretrained(
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- 'NaughtyDog97/FormalEnhencedGPS',
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  torch_dtype=torch.float16, # float32 for cpu
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  device_map='auto',
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  trust_remote_code=True)
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  tokenizer = AutoTokenizer.from_pretrained(
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- 'NaughtyDog97/FormalEnhencedGPS',
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  trust_remote_code=True)
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  # text prompt
@@ -144,12 +144,12 @@ formalization_tokenizer = AutoTokenizer.from_pretrained(
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  reason_model = AutoModelForCausalLM.from_pretrained(
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- 'NaughtyDog97/FormalEnhencedGPS',
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  torch_dtype=torch.float16, # float32 for cpu
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  device_map='auto',
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  trust_remote_code=True)
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  reason_tokenizer = AutoTokenizer.from_pretrained(
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- 'NaughtyDog97/FormalEnhencedGPS',
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  trust_remote_code=True)
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@@ -229,4 +229,4 @@ print(f'Reasoning steps is\n{respones}')
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  ## Performance
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  | | Q => Predicted CDL + CoT Answer | Q + Predicted CDL => CoT Answer | Q + Predicted CDL => Calibrated CDL + CoT Answer |
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  |-----|-------------------------------------|--------------------------------------|------------------------------------------------------|
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- | siglip-0.4B-yi1.5-9B | 62.62/72.65 | 63.11/75.40 | 63.43/75.73 |
 
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  # create model
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  model = AutoModelForCausalLM.from_pretrained(
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+ 'NaughtyDog97/FormalEnhencedGPS-9B',
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  torch_dtype=torch.float16, # float32 for cpu
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  device_map='auto',
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  trust_remote_code=True)
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  tokenizer = AutoTokenizer.from_pretrained(
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+ 'NaughtyDog97/FormalEnhencedGPS-9B',
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  trust_remote_code=True)
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  # text prompt
 
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  reason_model = AutoModelForCausalLM.from_pretrained(
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+ 'NaughtyDog97/FormalEnhencedGPS-9B',
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  torch_dtype=torch.float16, # float32 for cpu
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  device_map='auto',
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  trust_remote_code=True)
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  reason_tokenizer = AutoTokenizer.from_pretrained(
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+ 'NaughtyDog97/FormalEnhencedGPS-9B',
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  trust_remote_code=True)
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  ## Performance
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  | | Q => Predicted CDL + CoT Answer | Q + Predicted CDL => CoT Answer | Q + Predicted CDL => Calibrated CDL + CoT Answer |
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  |-----|-------------------------------------|--------------------------------------|------------------------------------------------------|
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+ | siglip-0.4B-yi1.5-9B | 63.92/73.30 | 63.59/74.27 | 65.05/75.24 |
config.json CHANGED
@@ -1,5 +1,5 @@
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- "_name_or_path": "NaughtyDog97/FormalEnhencedGPS",
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  "architectures": [
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  "FegeoLlamaForCausalLM"
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  ],
 
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