nielsr HF Staff commited on
Commit
f0d63a0
·
verified ·
1 Parent(s): 02e9916

Add Hugging Face paper link and clarify repos

Browse files

This PR adds a link to the Hugging Face paper page for better discoverability and clarifies which repo is used for training/finetuning and which contains the GGUF weights.

Files changed (1) hide show
  1. README.md +7 -6
README.md CHANGED
@@ -1,15 +1,15 @@
1
  ---
2
- license: mit
3
- license_link: https://huggingface.co/microsoft/bitnet-b1.58-2B-4T/blob/main/LICENSE
4
  language:
5
  - en
 
 
 
6
  pipeline_tag: text-generation
7
  tags:
8
  - chat
9
  - bitnet
10
  - text-generation
11
  - large-language-model
12
- library_name: transformers
13
  ---
14
 
15
  # BitNet b1.58 2B4T - Scaling Native 1-bit LLM
@@ -18,7 +18,7 @@ This repository contains the weights for **BitNet b1.58 2B4T**, the first open-s
18
 
19
  Trained on a corpus of 4 trillion tokens, this model demonstrates that native 1-bit LLMs can achieve performance comparable to leading open-weight, full-precision models of similar size, while offering substantial advantages in computational efficiency (memory, energy, latency).
20
 
21
- ➡️ **Technical Report:** [BitNet b1.58 2B4T Technical Report](https://arxiv.org/abs/2504.12285)
22
 
23
  ➡️ **Official Inference Code:** [microsoft/BitNet (bitnet.cpp)](https://github.com/microsoft/BitNet)
24
 
@@ -98,7 +98,8 @@ chat_input = tokenizer(prompt, return_tensors="pt").to(model.device)
98
  # Generate response
99
  chat_outputs = model.generate(**chat_input, max_new_tokens=50)
100
  response = tokenizer.decode(chat_outputs[0][chat_input['input_ids'].shape[-1]:], skip_special_tokens=True) # Decode only the response part
101
- print("\nAssistant Response:", response)
 
102
  ```
103
 
104
  ## How to Use (with `bitnet.cpp`)
@@ -141,4 +142,4 @@ BitNet b1.58 2B4T was evaluated against leading open-weight full-precision LLMs
141
  The model weights and code are released under the [MIT License](https://huggingface.co/microsoft/bitnet-b1.58-2B-4T/blob/main/LICENSE).
142
 
143
  ## Disclaimer
144
- 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.
 
1
  ---
 
 
2
  language:
3
  - en
4
+ library_name: transformers
5
+ license: mit
6
+ license_link: https://huggingface.co/microsoft/bitnet-b1.58-2B-4T/blob/main/LICENSE
7
  pipeline_tag: text-generation
8
  tags:
9
  - chat
10
  - bitnet
11
  - text-generation
12
  - large-language-model
 
13
  ---
14
 
15
  # BitNet b1.58 2B4T - Scaling Native 1-bit LLM
 
18
 
19
  Trained on a corpus of 4 trillion tokens, this model demonstrates that native 1-bit LLMs can achieve performance comparable to leading open-weight, full-precision models of similar size, while offering substantial advantages in computational efficiency (memory, energy, latency).
20
 
21
+ ➡️ **Technical Report:** [BitNet b1.58 2B4T Technical Report](https://arxiv.org/abs/2504.12285) ➡️ **Hugging Face Paper:** [Hugging Face Paper](https://huggingface.co/papers/2504.12285)
22
 
23
  ➡️ **Official Inference Code:** [microsoft/BitNet (bitnet.cpp)](https://github.com/microsoft/BitNet)
24
 
 
98
  # Generate response
99
  chat_outputs = model.generate(**chat_input, max_new_tokens=50)
100
  response = tokenizer.decode(chat_outputs[0][chat_input['input_ids'].shape[-1]:], skip_special_tokens=True) # Decode only the response part
101
+ print("
102
+ Assistant Response:", response)
103
  ```
104
 
105
  ## How to Use (with `bitnet.cpp`)
 
142
  The model weights and code are released under the [MIT License](https://huggingface.co/microsoft/bitnet-b1.58-2B-4T/blob/main/LICENSE).
143
 
144
  ## Disclaimer
145
+ 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.