* fix: Correct method argument types in generation and validation
In the `generation.rs` and `validation.rs` files, corrected the argument types
passed to the `decode` method. Replaced `Vec<u32>` with `&[u32]` using the
`as_ref()` method to match the expected argument types. This resolves the
mismatched types compilation error during the Rust build process.
Closes
[#9](https://github.com/Preemo-Inc/text-generation-inference/issues/9)
* Update benchmark/src/generation.rs
Co-authored-by: Yang, Bo <pop.atry@gmail.com>
* Update router/src/validation.rs
Co-authored-by: Yang, Bo <pop.atry@gmail.com>
---------
Co-authored-by: Yang, Bo <pop.atry@gmail.com>
Currently `BLOOMSharded` is a subclass of `CausalLM`, while it skips `CausalLM`'s constructor. This is a supprising behavior that we might want to avoid.
This PR extract `CausalLM`'s constructor to `AutoCausalLM` to detect settings from `model_id`, so that we don't have to skip `CausalLM`'s constructor.
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As per title.
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- Current PR is not great because we're side stepping the
`Weights.__init__` but Weights shouldn't requires anything related
to the config or the model_id as it aims to be a simple Wrapper
over multi file loading.
- Ideal solution would be to use something like Rust enum
```
enum Quantize{
Bitandbytes(Bitsandbytes),
GPTQ(bits: usize, groupsize: usize)
```
And passing that around during load. Unfortunately we don't
have access to this, so for now, side-stepping seems easier.
- Re-enabling groupsize<0 with exllama (confirmed it works.)
Helps #601
In next steps we should make sure our quantization script uses that
format and make it standard.
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This PR directly load GPTBigCode to specified device, avoiding moving
model between devices.
# What does this PR do?
This PR directly load GPTBigCode to specified device, avoiding moving
model between devices.
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Just trying to get the integration tests to pass.
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---------
Co-authored-by: Felix Marty <9808326+fxmarty@users.noreply.github.com>
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Fixes a bug appeared with MR #587 fixing issue #552.
See the discussion in #552.
With MR #587 the trust_remote_code variable is not passed to
AutoModelForCausalLM, but is found in the function signature. This
prevents models like falcon to be quantized, because trust_remote_code
is required. This MR fixes the issue.
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but should work on more configurations (no need for 2 GPUs, less RAM
usage).
# What does this PR do?
Reworking the quantization script so it's still universal (not llama
specific)
but should work on more configurations (no need for 2 GPUs, less RAM
usage).
Still need to investigate the potential differences in quantization
results.
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Michael Feil