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Update README.md

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  1. README.md +17 -3
README.md CHANGED
@@ -6,8 +6,22 @@ tags:
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  - MiniCPM
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  - ModelBest
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  - THUNLP
 
 
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  ---
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  <div align="center">
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  <h1>
@@ -95,9 +109,9 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
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  import torch
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  torch.manual_seed(0)
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- path = 'openbmb/MiniCPM-2B-dpo-bf16'
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  tokenizer = AutoTokenizer.from_pretrained(path)
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- model = AutoModelForCausalLM.from_pretrained(path, torch_dtype=torch.bfloat16, device_map='cuda', trust_remote_code=True)
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  responds, history = model.chat(tokenizer, "山东省最高的山是哪座山, 它比黄山高还是矮?差距多少?", temperature=0.8, top_p=0.8)
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  print(responds)
@@ -148,4 +162,4 @@ print(responds)
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  booktitle={OpenBMB Blog},
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  year={2024}
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  }
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- ```
 
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  - MiniCPM
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  - ModelBest
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  - THUNLP
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+ - mlx
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+ library_name: mlx
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  ---
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+ # Important:
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+ made a seperate repo, because the OG creators didn't merge the safensors variant commit from the huggingface team, and due to the model_type property not existing in the config, (for my MiniCPM implementatino in mlx-examples). This is all fixed here.
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+
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+ To use in mlx:
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+
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+ ```sh
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+ python -m mlx_lm.generate --model Isaak-Carter/MiniCPM-2B-sft-fp32-safetensors --prompt "hello"
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+ ```
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+
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+
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+
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+
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  <div align="center">
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  <h1>
 
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  import torch
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  torch.manual_seed(0)
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+ path = 'openbmb/MiniCPM-2B-dpo-fp32'
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  tokenizer = AutoTokenizer.from_pretrained(path)
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+ model = AutoModelForCausalLM.from_pretrained(path, torch_dtype=torch.float32, device_map='cuda', trust_remote_code=True)
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  responds, history = model.chat(tokenizer, "山东省最高的山是哪座山, 它比黄山高还是矮?差距多少?", temperature=0.8, top_p=0.8)
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  print(responds)
 
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  booktitle={OpenBMB Blog},
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  year={2024}
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  }
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+ ```