llmware
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bling-1b-0.1

Text Generation

text-generation-inference

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doberst commited on Sep 30, 2023

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@@ -70,8 +70,8 @@ BLING has not been designed for end consumer-oriented applications, and there ha
 The fastest way to get started with BLING is through direct import in transformers:
 from transformers import AutoTokenizer, AutoModelForCausalLM
-tokenizer = AutoTokenizer.from_pretrained("llmware/bling-1.4b-0.1")
-model = AutoModelForCausalLM.from_pretrained("llmware/bling-1.4b-0.1")
 The BLING model was fine-tuned with a simple "\<human> and \<bot> wrapper", so to get the best results, wrap inference entries as:

 The fastest way to get started with BLING is through direct import in transformers:
 from transformers import AutoTokenizer, AutoModelForCausalLM
+tokenizer = AutoTokenizer.from_pretrained("llmware/bling-1b-0.1")
+model = AutoModelForCausalLM.from_pretrained("llmware/bling-1b-0.1")
 The BLING model was fine-tuned with a simple "\<human> and \<bot> wrapper", so to get the best results, wrap inference entries as: