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Update all references to canonical models (#29001)

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* Script & Manual edition

* Update
This commit is contained in:
Lysandre Debut
2024-02-16 08:16:58 +01:00
committed by GitHub
parent 1e402b957d
commit f497f564bb
561 changed files with 2682 additions and 2687 deletions
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docs/source/ja/generation_strategies.md
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@@ -41,7 +41,7 @@ generateメソッドへの入力は、モデルのモダリティに依存しま
```python
>>> from transformers import AutoModelForCausalLM
>>> model = AutoModelForCausalLM.from_pretrained("distilgpt2")
>>> model = AutoModelForCausalLM.from_pretrained("distilbert/distilgpt2")
>>> model.generation_config
GenerationConfig {
"bos_token_id": 50256,
@@ -94,8 +94,8 @@ GenerationConfig {
```python
>>> from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, GenerationConfig
>>> tokenizer = AutoTokenizer.from_pretrained("t5-small")
>>> model = AutoModelForSeq2SeqLM.from_pretrained("t5-small")
>>> tokenizer = AutoTokenizer.from_pretrained("google-t5/t5-small")
>>> model = AutoModelForSeq2SeqLM.from_pretrained("google-t5/t5-small")
>>> translation_generation_config = GenerationConfig(
... num_beams=4,
@@ -132,8 +132,8 @@ GenerationConfig {
```python
>>> from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
>>> tok = AutoTokenizer.from_pretrained("gpt2")
>>> model = AutoModelForCausalLM.from_pretrained("gpt2")
>>> tok = AutoTokenizer.from_pretrained("openai-community/gpt2")
>>> model = AutoModelForCausalLM.from_pretrained("openai-community/gpt2")
>>> inputs = tok(["An increasing sequence: one,"], return_tensors="pt")
>>> streamer = TextStreamer(tok)
@@ -157,7 +157,7 @@ An increasing sequence: one, two, three, four, five, six, seven, eight, nine, te
>>> from transformers import AutoModelForCausalLM, AutoTokenizer
>>> prompt = "I look forward to"
>>> checkpoint = "distilgpt2"
>>> checkpoint = "distilbert/distilgpt2"
>>> tokenizer = AutoTokenizer.from_pretrained(checkpoint)
>>> inputs = tokenizer(prompt, return_tensors="pt")
@@ -177,7 +177,7 @@ An increasing sequence: one, two, three, four, five, six, seven, eight, nine, te
```python
>>> from transformers import AutoTokenizer, AutoModelForCausalLM
>>> checkpoint = "gpt2-large"
>>> checkpoint = "openai-community/gpt2-large"
>>> tokenizer = AutoTokenizer.from_pretrained(checkpoint)
>>> model = AutoModelForCausalLM.from_pretrained(checkpoint)
@@ -201,7 +201,7 @@ products or services, feel free to contact us at any time. We look forward to he
>>> from transformers import AutoTokenizer, AutoModelForCausalLM, set_seed
>>> set_seed(0) # For reproducibility
>>> checkpoint = "gpt2-large"
>>> checkpoint = "openai-community/gpt2-large"
>>> tokenizer = AutoTokenizer.from_pretrained(checkpoint)
>>> model = AutoModelForCausalLM.from_pretrained(checkpoint)
@@ -226,7 +226,7 @@ that\'s a terrible feeling."']
>>> from transformers import AutoModelForCausalLM, AutoTokenizer
>>> prompt = "It is astonishing how one can"
>>> checkpoint = "gpt2-medium"
>>> checkpoint = "openai-community/gpt2-medium"
>>> tokenizer = AutoTokenizer.from_pretrained(checkpoint)
>>> inputs = tokenizer(prompt, return_tensors="pt")
@@ -248,7 +248,7 @@ time."\n\nHe added: "I am very proud of the work I have been able to do in the l
>>> set_seed(0) # For reproducibility
>>> prompt = "translate English to German: The house is wonderful."
>>> checkpoint = "t5-small"
>>> checkpoint = "google-t5/t5-small"
>>> tokenizer = AutoTokenizer.from_pretrained(checkpoint)
>>> inputs = tokenizer(prompt, return_tensors="pt")