Update README.md

README.md

@@ -6,6 +6,9 @@ datasets:
 language:
 - fr
 - en
+metrics:
+- accuracy
+- perplexity
 ---
 
 # Mambaoutai 1.6B
@@ -20,14 +23,14 @@ You need to install `transformers` from `main` until `transformers=4.39.0` is re
 pip install git+https://github.com/huggingface/transformers@main
 ```
 
-We also recommend you to install both `causal_conv_1d` and `mamba-ssm` using: 
+We also recommend you to install both `causal-conv1d` and `mamba-ssm` using: 
 
 ```bash
 pip install causal-conv1d>=1.2.0
 pip install mamba-ssm
 ```
 
-If any of these two is not installed, the "eager" implementation will be used. Otherwise the more optimised `cuda` kernels will be used.
+If any of these two is not installed, the "eager" implementation will be used(not recommended). Otherwise the more optimised `cuda` kernels will be used.
 
 ### Generation
 
@@ -56,7 +59,8 @@ print(tokenizer.batch_decode(out))
 
 You can find some of the training checkpoints in the repo branch. On branch corresponding to the model at some point in time during training.
 
-You can do inference with these training checkpoints by adding the `revision` parameter to the `from_pretrained` method. For example, to load the model checkpoint after 30000 steps of pretraining, you can use the following code:
+You can do inference with these training checkpoints by adding the `revision` parameter to the `from_pretrained` method. 
+For example, to load the model checkpoint after 30000 steps of pretraining, you can use the following code:
 
 ```python
 from transformers import MambaConfig, MambaForCausalLM, AutoTokenizer