Narsil

import Metal
import MetalPerformanceShadersGraph



let type = MTLDataType.float;
let dataType = type;
var B = 2;
var M = 2;

Narsil

struct Tensor{
    id: usize
}


struct Linear{
    weight: Tensor,
    bias: Option<Tensor>,
}

Narsil

import http from 'k6/http';
import {sleep} from 'k6';
import { randomIntBetween } from 'https://jslib.k6.io/k6-utils/1.2.0/index.js';

const token = __ENV.API_TOKEN;

const MODEL_ID = "f-1" // Or "s-1"


export const options = {

Narsil

	.globl	<gemm_f16::gemm::f16::GEMM as lazy_static::LazyStatic>::initialize
	.p2align	2
<gemm_f16::gemm::f16::GEMM as lazy_static::LazyStatic>::initialize:
Lfunc_begin18:
	.cfi_startproc
	sub sp, sp, #48
	.cfi_def_cfa_offset 48
	stp x29, x30, [sp, #32]
	add x29, sp, #32
	.cfi_def_cfa w29, 16

Narsil

import torch
from transformers import AutoTokenizer, RobertaForMaskedLM, AutoConfig
from transformers.pipelines.base import infer_framework_load_model
from os import path
from huggingface_hub import hf_hub_download


def compare_models(pt_mdl, sf_mdl):
    # A blend of convert.py's generalized check_final_model with concrete usage example to demonstrate
    sf_dict = sf_mdl.state_dict()

Narsil

//
// Created by mfuntowicz on 3/28/23.
//
// ! Requires std=c++20 
#include <span>
#include "safetensors.hpp"
#include "nlohmann/json.hpp"

namespace huggingface::safetensors {

Narsil

#!/usr/bin/env python3
"""Toggle the bit at the specified offset.
Syntax: <cmdname> filename bit-offset"""

import sys
import os
import random

fname = sys.argv[1]
# Convert bit offset to bytes + leftover bits

Narsil

----------------
conll2003
===========================
StanfordAIMI/stanford-deidentifier-base
Results : 0.93 (4846/5233 (ignored 8808)
===========================
Davlan/bert-base-multilingual-cased-ner-hrl
Results : 0.98 (604/618 (ignored 13423)
===========================
dslim/bert-base-NER

Narsil

from safetensors import safe_open
import torch

from huggingface_hub import hf_hub_download

filenames = [
    "safety_checker/model.safetensors",
    "safety_checker/pytorch_model.bin",
    "vae/diffusion_pytorch_model.safetensors",
    "vae/diffusion_pytorch_model.bin",

Narsil

from huggingface_hub import hf_hub_download
from flax.serialization import msgpack_restore
from safetensors.flax import save_file
import numpy as np

filename = hf_hub_download("gpt2", filename="flax_model.msgpack")
with open(filename, "rb") as f:
    data = f.read()
flax_weights = msgpack_restore(data)