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switch-base-8

Text2Text Generation Transformers PyTorch
English switch_transformers Inference Endpoints
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ybelkada HF staff commited on
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Add correct class (#4)

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- Add correct class (8df8dbe6ddbb51430edb2ad6e0aa52a88df71d4a)

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  1. README.md +8 -8
README.md CHANGED
@@ -71,10 +71,10 @@ Find below some example scripts on how to use the model in `transformers`:
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  ```python
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- from transformers import AutoTokenizer, SwitchTransformersConditionalGeneration
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  tokenizer = AutoTokenizer.from_pretrained("google/switch-base-8")
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- model = SwitchTransformersConditionalGeneration.from_pretrained("google/switch-base-8")
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  input_text = "A <extra_id_0> walks into a bar a orders a <extra_id_1> with <extra_id_2> pinch of <extra_id_3>."
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  input_ids = tokenizer(input_text, return_tensors="pt").input_ids
@@ -93,10 +93,10 @@ print(tokenizer.decode(outputs[0]))
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  ```python
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  # pip install accelerate
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- from transformers import AutoTokenizer, SwitchTransformersConditionalGeneration
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  tokenizer = AutoTokenizer.from_pretrained("google/switch-base-8")
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- model = SwitchTransformersConditionalGeneration.from_pretrained("google/switch-base-8", device_map="auto")
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  input_text = "A <extra_id_0> walks into a bar a orders a <extra_id_1> with <extra_id_2> pinch of <extra_id_3>."
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  input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(0)
@@ -117,10 +117,10 @@ print(tokenizer.decode(outputs[0]))
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  ```python
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  # pip install accelerate
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- from transformers import AutoTokenizer, SwitchTransformersConditionalGeneration
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  tokenizer = AutoTokenizer.from_pretrained("google/switch-base-8")
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- model = SwitchTransformersConditionalGeneration.from_pretrained("google/switch-base-8", device_map="auto", torch_dtype=torch.float16)
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  input_text = "A <extra_id_0> walks into a bar a orders a <extra_id_1> with <extra_id_2> pinch of <extra_id_3>."
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  input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(0)
@@ -139,10 +139,10 @@ print(tokenizer.decode(outputs[0]))
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  ```python
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  # pip install bitsandbytes accelerate
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- from transformers import AutoTokenizer, SwitchTransformersConditionalGeneration
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  tokenizer = AutoTokenizer.from_pretrained("google/switch-base-8")
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- model = SwitchTransformersConditionalGeneration.from_pretrained("google/switch-base-8", device_map="auto")
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  input_text = "A <extra_id_0> walks into a bar a orders a <extra_id_1> with <extra_id_2> pinch of <extra_id_3>."
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  input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(0)
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  ```python
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+ from transformers import AutoTokenizer, SwitchTransformersForConditionalGeneration
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  tokenizer = AutoTokenizer.from_pretrained("google/switch-base-8")
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+ model = SwitchTransformersForConditionalGeneration.from_pretrained("google/switch-base-8")
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  input_text = "A <extra_id_0> walks into a bar a orders a <extra_id_1> with <extra_id_2> pinch of <extra_id_3>."
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  input_ids = tokenizer(input_text, return_tensors="pt").input_ids
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  ```python
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  # pip install accelerate
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+ from transformers import AutoTokenizer, SwitchTransformersForConditionalGeneration
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  tokenizer = AutoTokenizer.from_pretrained("google/switch-base-8")
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+ model = SwitchTransformersForConditionalGeneration.from_pretrained("google/switch-base-8", device_map="auto")
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  input_text = "A <extra_id_0> walks into a bar a orders a <extra_id_1> with <extra_id_2> pinch of <extra_id_3>."
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  input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(0)
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  ```python
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  # pip install accelerate
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+ from transformers import AutoTokenizer, SwitchTransformersForConditionalGeneration
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  tokenizer = AutoTokenizer.from_pretrained("google/switch-base-8")
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+ model = SwitchTransformersForConditionalGeneration.from_pretrained("google/switch-base-8", device_map="auto", torch_dtype=torch.float16)
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  input_text = "A <extra_id_0> walks into a bar a orders a <extra_id_1> with <extra_id_2> pinch of <extra_id_3>."
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  input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(0)
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  ```python
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  # pip install bitsandbytes accelerate
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+ from transformers import AutoTokenizer, SwitchTransformersForConditionalGeneration
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  tokenizer = AutoTokenizer.from_pretrained("google/switch-base-8")
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+ model = SwitchTransformersForConditionalGeneration.from_pretrained("google/switch-base-8", device_map="auto")
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  input_text = "A <extra_id_0> walks into a bar a orders a <extra_id_1> with <extra_id_2> pinch of <extra_id_3>."
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  input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(0)