Text Generation
Transformers.js
ONNX
llama
webgpu
q4f16
gptq
tool-calling
experimental
conversational
Instructions to use webbrain-one/webbrain-compass-tiny-v2.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use webbrain-one/webbrain-compass-tiny-v2.1 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('text-generation', 'webbrain-one/webbrain-compass-tiny-v2.1');
File size: 1,920 Bytes
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// Licensed under the MIT License.
import { Tensor } from './tensor-impl.js';
/**
* calculate size from dims.
*
* @param dims the dims array. May be an illegal input.
*/
export const calculateSize = (dims) => {
let size = 1;
for (let i = 0; i < dims.length; i++) {
const dim = dims[i];
if (typeof dim !== 'number' || !Number.isSafeInteger(dim)) {
throw new TypeError(`dims[${i}] must be an integer, got: ${dim}`);
}
if (dim < 0) {
throw new RangeError(`dims[${i}] must be a non-negative integer, got: ${dim}`);
}
size *= dim;
}
return size;
};
/**
* implementation of Tensor.reshape()
*/
export const tensorReshape = (tensor, dims) => {
switch (tensor.location) {
case 'cpu':
return new Tensor(tensor.type, tensor.data, dims);
case 'cpu-pinned':
return new Tensor({
location: 'cpu-pinned',
data: tensor.data,
type: tensor.type,
dims,
});
case 'texture':
return new Tensor({
location: 'texture',
texture: tensor.texture,
type: tensor.type,
dims,
});
case 'gpu-buffer':
return new Tensor({
location: 'gpu-buffer',
gpuBuffer: tensor.gpuBuffer,
type: tensor.type,
dims,
});
case 'ml-tensor':
return new Tensor({
location: 'ml-tensor',
mlTensor: tensor.mlTensor,
type: tensor.type,
dims,
});
default:
throw new Error(`tensorReshape: tensor location ${tensor.location} is not supported`);
}
};
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