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model usage

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  1. README.md +4 -5
README.md CHANGED
@@ -112,15 +112,14 @@ This model was trained using [OpenLM](https://github.com/mlfoundations/open_lm/)
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  ```python
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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  tokenizer = AutoTokenizer.from_pretrained("tri-ml/mamba-7b-rw")
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- model = AutoModelForCausalLM.from_pretrained("tri-ml/mamba-7b-rw").cuda()
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- inputs = tokenizer(["A beautiful flower"], return_tensors="pt")
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- gen_kwargs = {"max_length": 128, "top_p": 0.8, "temperature": 0.8, "do_sample": True, "repetition_penalty": 1.1}
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  output = model.generate(inputs['input_ids'], **gen_kwargs)
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  output = tokenizer.decode(output[0].tolist(), skip_special_tokens=True)
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  print(output)
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- # <s> A beautiful flower box made of white rose wood. It is a perfect gift for weddings, birthdays and anniversaries.
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- # All the roses are from our farm Roses Flanders. Therefor you know that these flowers last much longer than those in store or online!</s>
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  ```
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  ```python
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  from transformers import AutoTokenizer, AutoModelForCausalLM
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  tokenizer = AutoTokenizer.from_pretrained("tri-ml/mamba-7b-rw")
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+ model = AutoModelForCausalLM.from_pretrained("tri-ml/mamba-7b-rw")
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+ inputs = tokenizer(["The Toyota Supra"], return_tensors="pt")
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+ gen_kwargs = {"max_new_tokens": 50, "top_p": 0.8, "temperature": 0.8, "do_sample": True, "repetition_penalty": 1.1}
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  output = model.generate(inputs['input_ids'], **gen_kwargs)
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  output = tokenizer.decode(output[0].tolist(), skip_special_tokens=True)
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  print(output)
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+ # The Toyota Supra is a sports car that has been in production since 1978. The car was discontinued in 2002, but it has recently been revived and will be available again in 2020. The Supra has always been known for its powerful engines and agile handling.
 
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  ```
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