ce960be0a5
feat(bloom): use torch.nn.Linear and torch.nn.GELU ( #33 )
2023-01-26 15:33:45 +01:00
1f570d181f
fix(server): Fix position ids ( #28 )
2023-01-20 15:35:22 +01:00
15511edc01
feat(server): Support SantaCoder ( #26 )
2023-01-20 12:24:39 +01:00
e6d3eb5d5d
fix(server): Minor refactorization using new_zeros ( #24 )
...
- Fix some type hints, in particular base tokenizer class
- Make use of `tensor.new_zero/empty` methods
- Simplify env var string parsing in launcher
2023-01-17 09:10:22 +01:00
fcc2c5fcbf
feat(launcher): Log server stdout ( #19 )
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Co-authored-by: Nick Hill <nickhill@us.ibm.com>
2023-01-05 12:01:23 +01:00
b94f30215f
fix(server): Use cleanup_tokenization_spaces=False for lossless decoding ( #13 )
...
Fixes #12 in the easiest way I could think of.
2023-01-03 11:07:05 +01:00
686cc66717
fix(server): Check for device type correctly when determining initial padding ( #16 )
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AFAIK there is no torch device type called "gpu".
2022-12-30 19:30:42 +01:00
611e21cb13
fix(server): Fix stop sequences ( #11 )
2022-12-16 16:03:39 +01:00
32a253063d
feat: Return logprobs ( #8 )
2022-12-15 17:03:56 +01:00
718096f695
feat: Support stop sequences ( #7 )
2022-12-12 18:25:22 +01:00
042180d88f
fix(server): Only pad to multiple of 8 on GPUs
2022-12-08 19:37:37 +01:00
a2985036aa
feat(server): Add model tests ( #6 )
2022-12-08 18:49:33 +01:00
31d76e238d
fix(batching): Avoid theoretical hang in batcher loop ( #5 )
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- Avoid theoretical hang in batcher loop
- Avoid a couple of clones in the router generate method
- Keep attention mask tensors as integers
- Remove num_heads attribute
Co-authored-by: OlivierDehaene <Olivier.dehaene@gmail.com>
2022-12-05 10:10:59 +01:00
daa1d81d5e
feat(server): Support Galactica ( #4 )
2022-12-01 19:31:54 +01:00
dccd5c2b1a
feat(server): Clarify CausalLMBatch concatenate method
2022-11-09 18:24:07 +01:00
fa43fb71be
fix(server): Fix Transformers fork version
2022-11-08 17:42:38 +01:00
4236e41b0d
feat(server): Improved doc
2022-11-07 12:53:56 +01:00
427d7cc444
feat(server): Support AutoModelForSeq2SeqLM
2022-11-04 18:03:04 +01:00
c5665f5c8b
feat(server): Support generic AutoModelForCausalLM
2022-11-04 14:22:47 +01:00
755fc0e403
fix(models): Revert buggy support for AutoModel
2022-11-03 16:07:54 +01:00
b3b7ea0d74
feat: Use json formatter by default in docker image
2022-11-02 17:29:56 +01:00
3cf6368c77
feat(server): Support all AutoModelForCausalLM on a best effort basis
2022-10-28 19:24:00 +02:00
OlivierDehaene