This model is based on [bigscience/bloomz-7b1-mt](https://huggingface.co/bigscience/bloom-7b1). To make it more accessible and efficient for certain Chinese , we have pruned its original vocabulary from 250,880 tokens to 46,145 tokens using Chinese corpus data as follow [bloom-6b4-zh](https://huggingface.co/Langboat/bloom-6b4-zh). This reduction in vocabulary size has helped to significantly reduce the GPU memory usage required to run the model. As a result, the total number of parameters in the model is now 6 billion 4.



基于 [bigscience/bloomz-7b1-mt](https://huggingface.co/bigscience/bloom-7b1)，修建embeddings层到 46145，主要保留中文相关的tokens映射。修建后参数为6B4。



# How to use

```python
from transformers import BloomTokenizerFast, BloomForCausalLM

tokenizer = BloomTokenizerFast.from_pretrained('enze/bloomz-6b4-zh')
model = BloomForCausalLM.from_pretrained('enze/bloomz-6b4-zh')

print(tokenizer.batch_decode(model.generate(tokenizer.encode('中国的首都是', return_tensors='pt'))))
```
{"license": "bigscience-bloom-rail-1.0"}
transformers pytorch bloom text-generation license:bigscience-bloom-rail-1.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #bloom #text-generation #license-bigscience-bloom-rail-1.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 

This model is based on bigscience/bloomz-7b1-mt. To make it more accessible and efficient for certain Chinese , we have pruned its original vocabulary from 250,880 tokens to 46,145 tokens using Chinese corpus data as follow bloom-6b4-zh. This reduction in vocabulary size has helped to significantly reduce the GPU memory usage required to run the model. As a result, the total number of parameters in the model is now 6 billion 4.



基于 bigscience/bloomz-7b1-mt，修建embeddings层到 46145，主要保留中文相关的tokens映射。修建后参数为6B4。



# How to use


# How to use
TAGS
#transformers #pytorch #bloom #text-generation #license-bigscience-bloom-rail-1.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # How to use
TAGS
#transformers #pytorch #bloom #text-generation #license-bigscience-bloom-rail-1.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# How to use