sroecker

from numpy import *

class BLUE:
    """A simple implementation of BLUE for 2 measurements"""
 
    def __init__(self):
        self.values = matrix([0,0])
        self.ematrix = matrix([[0,0],[0,0]])

    def AddMeasurement(self,v1,v2):

sroecker

Verifying that +sroecker is my openname (Bitcoin username). https://onename.io/sroecker

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def upload_dataset_from_catalog(self, dataset):
    import json
    import time
    client = dr.Client()
    res = client.post(client.endpoint + "/projects/{}/predictionDatasets/datasetUploads/".format(self.id), json={"datasetId": dataset.id})
    dataset_id = json.loads(res.text)['datasetId']
    while dataset_id not in [ds.id for ds in self.get_datasets()]:
        time.sleep(1)
    return dataset_id
dr.Project.upload_dataset_from_catalog = upload_dataset_from_catalog

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def upload_dataset_from_catalog(self, dataset):
    import json
    import time
    # client = dr.Client()
    res = client.post(client.endpoint + "/projects/{}/predictionDatasets/datasetUploads/".format(self.id), json={"datasetId": dataset.id})
    dataset_id = json.loads(res.text)['datasetId']
    while dataset_id not in [ds.id for ds in self.get_datasets()]:
        time.sleep(1)
    return dataset_id
def get_prediction_explanations(self, dataset_id):

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import json
import requests
import collections

class BearerAuth(requests.auth.AuthBase):
    def __init__(self, token):
        self.token = token
    def __call__(self, r):
        r.headers['Authorization'] = 'Bearer ' + self.token
        return r

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import torch

print("pytorch version: " + torch.__version__)
print("CUDA available: " + str(torch.cuda.is_available()))
print("device count: " + str(torch.cuda.device_count()))
print("current device: " + str(torch.cuda.current_device()))
print("device name: " + torch.cuda.get_device_name(torch.cuda.current_device()))
print("backend:")
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
print(device)

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#!/bin/bash
git clone https://github.com/continuedev/continue
npm config set prefix ~/.local
sh continue/install-dependencies.sh
cd continue/extensions/vscode
node scripts/prepackage.js
npm install @vscode/vsce
PATH=$PATH:~/.local/bin/
npm install yarn
node scripts/package.js

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podman run --rm --device nvidia.com/gpu=all --security-opt=label=disable --mount type=bind,src="${PWD}",target=/workspace/axol  
otl -v ${HOME}/.cache/huggingface:/root/.cache/huggingface winglian/axolotl:main-py3.10-cu118-2.0.1 accelerate launch -m axolotl.cli.train examples/openllam  
a-3b/lora.yml

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import modal

app = modal.App(name="pokemon-eval")

moondream_image = modal.Image.micromamba(
    python_version="3.11"
).apt_install(
    "git"
).micromamba_install(
    "cudatoolkit",

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import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
import xxhash
from tqdm import tqdm

# load moondream model
model_id = "vikhyatk/moondream2"
revision = "2024-05-20"

model = AutoModelForCausalLM.from_pretrained(