Unverified Commit 73d84c6e authored by Nicolas Patry's avatar Nicolas Patry Committed by GitHub
Browse files

Hotfixes for santacoder/bigcode. (#294)

# What does this PR do?

Hotfixes:

- Uses `model_type`=`gpt_bigcode` for more general usage.
- Hotfixes linked lm_head vs wte_embedding (safetensors file do not
contain the key, correctly when the file is sharded, where as pytorch
copies the tensor)


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Fixes # (issue)


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Did you read the [contributor
guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
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      to it if that's the case.
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- [ ] Did you write any new necessary tests?


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---------
Co-authored-by: default avatarUbuntu <ubuntu@ip-172-31-41-161.ec2.internal>
Co-authored-by: default avatarOlivierDehaene <olivier@huggingface.co>
parent 22c4fd07
...@@ -99,7 +99,7 @@ def get_model( ...@@ -99,7 +99,7 @@ def get_model(
else: else:
return Galactica(model_id, revision, quantize=quantize) return Galactica(model_id, revision, quantize=quantize)
if "bigcode" in model_id: if model_id.startswith("bigcode/"):
if sharded: if sharded:
if not FLASH_ATTENTION: if not FLASH_ATTENTION:
raise NotImplementedError( raise NotImplementedError(
...@@ -113,6 +113,17 @@ def get_model( ...@@ -113,6 +113,17 @@ def get_model(
config = AutoConfig.from_pretrained(model_id, revision=revision) config = AutoConfig.from_pretrained(model_id, revision=revision)
model_type = config.model_type model_type = config.model_type
if model_type == "gpt_bigcode":
if sharded:
if not FLASH_ATTENTION:
raise NotImplementedError(
FLASH_ATT_ERROR_MESSAGE.format(f"Sharded Santacoder")
)
return FlashSantacoderSharded(model_id, revision, quantize=quantize)
else:
santacoder_cls = FlashSantacoder if FLASH_ATTENTION else SantaCoder
return santacoder_cls(model_id, revision, quantize=quantize)
if model_type == "bloom": if model_type == "bloom":
if sharded: if sharded:
return BLOOMSharded(model_id, revision, quantize=quantize) return BLOOMSharded(model_id, revision, quantize=quantize)
......
...@@ -376,6 +376,9 @@ class FlashSantacoderSharded(FlashSantacoder): ...@@ -376,6 +376,9 @@ class FlashSantacoderSharded(FlashSantacoder):
else: else:
module._buffers[param_name] = tensor module._buffers[param_name] = tensor
model.lm_head.weight = torch.nn.Parameter(model.transformer.wte.weight)
uninitialized_parameters = [] uninitialized_parameters = []
for n, p in model.named_parameters(): for n, p in model.named_parameters():
if p.data.device == torch.device("meta"): if p.data.device == torch.device("meta"):
......
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