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Doc styler examples (#14953)

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* Fix bad examples

* Add black formatting to style_doc

* Use first nonempty line

* Put it at the right place

* Don't add spaces to empty lines

* Better templates

* Deal with triple quotes in docstrings

* Result of style_doc

* Enable mdx treatment and fix code examples in MDXs

* Result of doc styler on doc source files

* Last fixes

* Break copy from
This commit is contained in:
Sylvain Gugger
2021-12-27 19:07:46 -05:00
committed by GitHub
parent e13f72fbff
commit b5e2b183af
211 changed files with 2738 additions and 1711 deletions
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35
docs/source/model_doc/gptj.mdx
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@@ -33,7 +33,9 @@ Tips:
>>> from transformers import GPTJForCausalLM
>>> import torch
>>> model = GPTJForCausalLM.from_pretrained("EleutherAI/gpt-j-6B", revision="float16", torch_dtype=torch.float16, low_cpu_mem_usage=True)
>>> model = GPTJForCausalLM.from_pretrained(
... "EleutherAI/gpt-j-6B", revision="float16", torch_dtype=torch.float16, low_cpu_mem_usage=True
... )
```
- The model should fit on 16GB GPU for inference. For training/fine-tuning it would take much more GPU RAM. Adam
@@ -56,16 +58,24 @@ model.
```python
>>> from transformers import AutoModelForCausalLM, AutoTokenizer
>>> model = AutoModelForCausalLM.from_pretrained("EleutherAI/gpt-j-6B")
>>> tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-j-6B")
>>> prompt = "In a shocking finding, scientists discovered a herd of unicorns living in a remote, " \
... "previously unexplored valley, in the Andes Mountains. Even more surprising to the " \
... "researchers was the fact that the unicorns spoke perfect English."
>>> prompt = (
... "In a shocking finding, scientists discovered a herd of unicorns living in a remote, "
... "previously unexplored valley, in the Andes Mountains. Even more surprising to the "
... "researchers was the fact that the unicorns spoke perfect English."
... )
>>> input_ids = tokenizer(prompt, return_tensors="pt").input_ids
>>> gen_tokens = model.generate(input_ids, do_sample=True, temperature=0.9, max_length=100,)
>>> gen_tokens = model.generate(
... input_ids,
... do_sample=True,
... temperature=0.9,
... max_length=100,
... )
>>> gen_text = tokenizer.batch_decode(gen_tokens)[0]
```
@@ -78,13 +88,20 @@ model.
>>> model = GPTJForCausalLM.from_pretrained("EleutherAI/gpt-j-6B", torch_dtype=torch.float16)
>>> tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-j-6B")
>>> prompt = "In a shocking finding, scientists discovered a herd of unicorns living in a remote, " \
... "previously unexplored valley, in the Andes Mountains. Even more surprising to the " \
... "researchers was the fact that the unicorns spoke perfect English."
>>> prompt = (
... "In a shocking finding, scientists discovered a herd of unicorns living in a remote, "
... "previously unexplored valley, in the Andes Mountains. Even more surprising to the "
... "researchers was the fact that the unicorns spoke perfect English."
... )
>>> input_ids = tokenizer(prompt, return_tensors="pt").input_ids
>>> gen_tokens = model.generate(input_ids, do_sample=True, temperature=0.9, max_length=100,)
>>> gen_tokens = model.generate(
... input_ids,
... do_sample=True,
... temperature=0.9,
... max_length=100,
... )
>>> gen_text = tokenizer.batch_decode(gen_tokens)[0]
```