GGUF
Composer
MosaicML
llm-foundry
maddes8cht commited on
Commit
53db19b
1 Parent(s): 5061fae

"Update README.md"

Browse files
Files changed (1) hide show
  1. README.md +5 -12
README.md CHANGED
@@ -31,21 +31,14 @@ I'm constantly enhancing these model descriptions to provide you with the most r
31
  - Model creator: [mosaicml](https://huggingface.co/mosaicml)
32
  - Original model: [mpt-30b-chat](https://huggingface.co/mosaicml/mpt-30b-chat)
33
 
34
- # Important Update for Falcon Models in llama.cpp Versions After October 18, 2023
35
 
36
- As noted on the [Llama.cpp GitHub repository](https://github.com/ggerganov/llama.cpp#hot-topics), all new Llama.cpp releases after October 18, 2023, will require a re-quantization due to the new BPE tokenizer.
37
 
38
- **Good news!** I am glad that my re-quantization process for Falcon Models is nearly complete. Download the latest quantized models to ensure compatibility with recent llama.cpp software.
39
-
40
- **Key Points:**
41
-
42
- - **Stay Informed:** Keep an eye on software application release schedules using llama.cpp libraries.
43
- - **Monitor Upload Times:** Re-quantization is *almost* done. Watch for updates on my Hugging Face Model pages.
44
-
45
- **Important Compatibility Note:** Old software will work with old Falcon models, but expect updated software to exclusively support the new models.
46
-
47
- This change primarily affects **Falcon** and **Starcoder** models, with other models remaining unaffected.
48
 
 
49
 
50
 
51
 
 
31
  - Model creator: [mosaicml](https://huggingface.co/mosaicml)
32
  - Original model: [mpt-30b-chat](https://huggingface.co/mosaicml/mpt-30b-chat)
33
 
34
+ MPT-7b and MPT-30B are part of the family of Mosaic Pretrained Transformer (MPT) models, which use a modified transformer architecture optimized for efficient training and inference.
35
 
 
36
 
37
+ ---
38
+ # Brief
39
+ The MPT-7B and MPT-30B Models are part of the family of Mosaic Pretrained Transformer (MPT) models, which use a modified transformer architecture optimized for efficient training and inference.
 
 
 
 
 
 
 
40
 
41
+ ---
42
 
43
 
44