Update README.md

README.md

@@ -82,13 +82,13 @@ from h2oai_pipeline import H2OTextGenerationPipeline
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 tokenizer = AutoTokenizer.from_pretrained(
-    "PAIXAI/Astrid-Mistral-7B,
+    "PAIXAI/Astrid-Mistral-7B",
     use_fast=True,
     padding_side="left",
     trust_remote_code=True,
 )
 model = AutoModelForCausalLM.from_pretrained(
-    "PAIXAI/Astrid-Mistral-7B,
+    "PAIXAI/Astrid-Mistral-7B",
     torch_dtype="auto",
     device_map={"": "cuda:0"},
     trust_remote_code=True,
@@ -114,7 +114,7 @@ You may also construct the pipeline from the loaded model and tokenizer yourself
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
-model_name = "PAIXAI/Astrid-Mistral-7B  # either local folder or huggingface model name
+model_name = "PAIXAI/Astrid-Mistral-7B" # either local folder or huggingface model name
 # Important: The prompt needs to be in the same format the model was trained with.
 # You can find an example prompt in the experiment logs.
 prompt = "<|prompt|>How are you?<|im_end|><|answer|>"