huggingface/candle
1
0
Fork 0
mirror of https://github.com/huggingface/candle.git synced 2025-06-15 10:26:33 +00:00
Code Issues Packages Projects Releases Wiki Activity

Typos and format and CD only when PR lands.

Browse Source
This commit is contained in:
Nicolas Patry
2023-08-02 19:18:43 +02:00
parent 1b2b32e58d
commit dba31473d4
3 changed files with 6 additions and 8 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
.github/workflows/book-cd.yml vendored
View File

@ -1,7 +1,5 @@
name: Deploy Rust book
on:
# TODO put this back only when merging after this PR lands.
pull_request:
push:
branches:
- main

4
candle-book/src/inference/hub.md
View File

@ -67,8 +67,8 @@ let bias = weights.get("bert.encoder.layer.0.attention.self.query.bias").unwrap(
let linear = Linear::new(weight.clone(), Some(bias.clone()));
let input_ids = Tensor::zeros((3, 7680), DType::F32, &Device::Cpu).unwrap();
let output = linear.forward(&input_ids);
let input_ids = Tensor::zeros((3, 768), DType::F32, &Device::Cpu).unwrap();
let output = linear.forward(&input_ids).unwrap();
```
For a full reference, you can check out the full [bert](https://github.com/LaurentMazare/candle/tree/main/candle-examples/examples/bert) example.

8
candle-examples/src/lib.rs
View File

@ -73,8 +73,8 @@ let mmap = unsafe { Mmap::map(&file).unwrap() };
// Use safetensors directly
let tensors = SafeTensors::deserialize(&mmap[..]).unwrap();
let view = tensors
.tensor("bert.encoder.layer.0.attention.self.query.weight")
.unwrap();
.tensor("bert.encoder.layer.0.attention.self.query.weight")
.unwrap();
// We're going to load shard with rank 1, within a world_size of 4
// We're going to split along dimension 0 doing VIEW[start..stop, :]
@ -86,7 +86,7 @@ let mut tp_shape = view.shape().to_vec();
let size = tp_shape[0];
if size % world_size != 0 {
panic!("The dimension is not divisble by `world_size`");
panic!("The dimension is not divisble by `world_size`");
}
let block_size = size / world_size;
let start = rank * block_size;
@ -102,7 +102,7 @@ tp_shape[dim] = block_size;
// Convert safetensors Dtype to candle DType
let dtype: DType = dtype.try_into().unwrap();
// TODO: Implement from_buffer_iterator to we can skip the extra CPU alloc.
// TODO: Implement from_buffer_iterator so we can skip the extra CPU alloc.
let raw: Vec<u8> = iterator.into_iter().flatten().cloned().collect();
let tp_tensor = Tensor::from_raw_buffer(&raw, dtype, &tp_shape, &Device::Cpu).unwrap();
// ANCHOR_END: book_hub_3