llmware
/

dragon-yi-6b-v0

Text Generation

Inference Endpoints

Model card Files Files and versions Community

doberst commited on Nov 16, 2023

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b155a19

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1 Parent(s): 415157f

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@@ -79,8 +79,8 @@ Any model can provide inaccurate or incomplete information, and should be used i
 The fastest way to get started with BLING is through direct import in transformers:
     from transformers import AutoTokenizer, AutoModelForCausalLM
-    tokenizer = AutoTokenizer.from_pretrained("dragon-yi-6b-0.1")
-    model = AutoModelForCausalLM.from_pretrained("dragon-yi-6b-0.1")
 Please refer to the generation_test .py files in the Files repository, which includes 200 samples and script to test the model.  The **generation_test_llmware_script.py** includes built-in llmware capabilities for fact-checking, as well as easy integration with document parsing and actual retrieval to swap out the test set for RAG workflow consisting of business documents.

 The fastest way to get started with BLING is through direct import in transformers:
     from transformers import AutoTokenizer, AutoModelForCausalLM
+    tokenizer = AutoTokenizer.from_pretrained("dragon-yi-6b-v0")
+    model = AutoModelForCausalLM.from_pretrained("dragon-yi-6b-v0")
 Please refer to the generation_test .py files in the Files repository, which includes 200 samples and script to test the model.  The **generation_test_llmware_script.py** includes built-in llmware capabilities for fact-checking, as well as easy integration with document parsing and actual retrieval to swap out the test set for RAG workflow consisting of business documents.