bit

README.md

@@ -68,8 +68,9 @@ Several versions of the model weights are available on Hugging Face:
 ### Requirements
 
 ```bash
-pip install git+https://github.com/huggingface/transformers.git@096f25ae1f501a084d8ff2dcaf25fbc2bd60eba4
+pip install git+https://github.com/shumingma/transformers.git
 ```
+We are actively working with the Hugging Face team to integrate the necessary code into the main `transformers` library. This installation method may change in the future.
 
 ### Example
 
@@ -150,6 +151,3 @@ The Bitnet model has an elevated defect rate when responding to election-critica
 
 ## Disclaimer
 We do not recommend using BitNet b1.58 in commercial or real-world applications without further testing and development. This model is intended for research and development purposes. While efforts have been made to align it using SFT and DPO, it may still produce outputs that are unexpected, biased, or inaccurate. Please use responsibly.
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-## Data Summary
-https://huggingface.co/microsoft/bitnet-b1.58-2B-4T/blob/main/data_summary_card.md

data_summary_card.md

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-# Data Summary for microsoft_bitnet-b1.58-2B-4T, bitnet-b1.58-2B-4T-gguf, bitnet-b1.58-2B-4T-bf16 
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-## 1. General information 
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-**1.0.1 Version of the Summary:** 1.0 
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-**1.0.2 Last update:** 16-Dec-2025 
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-## 1.1 Model Developer Identification 
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-**1.1.1 Model Developer name and contact details:** Microsoft Corporation at One Microsoft Way, Redmond, WA 98052. Tel: 425-882-8080. 
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-## 1.2 Model Identification 
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-**1.2.1 Versioned model name(s):** bitnet-b1.58-2B-4T 
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-**1.2.2 Model release date:** 01-May-2025 
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-## 1.3 Overall training data size and characteristics 
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-### 1.3.1 Size of dataset and characteristics 
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-**1.3.1.A Text training data size:** 1 billion to 10 trillion tokens 
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-**1.3.1.B Text training data content:** We used SmolLM-Corpus，dclm-baseline-1.0 and open-web-math datasets to train this model. 
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-**1.3.1.C Image training data size:** Not applicable. Images are not part of the training data 
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-**1.3.1.D Image training data content:** Not applicable 
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-**1.3.1.E Audio training data size:** Not applicable. Audio content is not part of the training data 
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-**1.3.1.F Audio training data content:** Not applicable 
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-**1.3.1.G Video training data size:** Not applicable. Videos are not part of the training data 
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-**1.3.1.H Video training data content:** Not applicable 
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-**1.3.1.I Other training data size:** Not applicable 
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-**1.3.1.J Other training data content:** Not applicable 
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-**1.3.2 Latest date of data acquisition/collection for model training:** 15-Jul-2024 
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-**1.3.3 Is data collection ongoing to update the model with new data collection after deployment?** No 
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-**1.3.4 Date the training dataset was first used to train the model:** 12-Jan-2025 
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-**1.3.5 Rationale or purpose of data selection:** The training corpus included publicly available text and code datasets to provide broad world knowledge and foundational language capabilities, with synthetic mathematical data to enhance reasoning. Selected datasets were emphasized later to refine performance 
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-## 2. List of data sources 
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-### 2.1 Publicly available datasets 
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-**2.1.1 Have you used publicly available datasets to train the model?** Yes 
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-## 2.2 Private non-publicly available datasets obtained from third parties 
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-### 2.2.1 Datasets commercially licensed by rights holders or their representatives 
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-**2.2.1.A Have you concluded transactional commercial licensing agreement(s) with rights holder(s) or with their representatives?** No 
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-### 2.2.2 Private datasets obtained from other third-parties 
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-**2.2.2.A Have you obtained private datasets from third parties that are not licensed as described in Section 2.2.1, such as data obtained from providers of private databases, or data intermediaries?** No 
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-## 2.3 Personal Information 
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-**2.3.1 Was personal data used to train the model?** Microsoft follows all relevant laws and regulations pertaining to personal information 
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-## 2.4 Synthetic data 
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-**2.4.1 Was any synthetic AI-generated data used to train the model?** No 
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-## 3. Data processing aspects 
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-### 3.1 Respect of reservation of rights from text and data mining exception or limitation 
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-**3.1.1 Does this dataset include any data protected by copyright, trademark, or patent?** Microsoft follows all required regulations and laws for processing data protected by copyright, trademark, or patent 
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-## 3.2 Other information 
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-**3.2.1 Does the dataset include information about consumer groups without revealing individual consumer identities?** Microsoft follows all required regulations and laws for protecting consumer identities 
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-**3.2.2 Was the dataset cleaned or modified before model training?** Yes 
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