Repository: sintel-dev/sigllm (language: python)

Issue:
Forecasting Module
### Description

In addition to directly finding anomalies in time series data, forecasting can be utilized for the same task. In many approaches for unsupervised time series anomaly detection, forecasting has been used to generate an alternative signal which then gets compared to the original one. If there are discrepancies between the two signals, this is an indication of where the anomaly might be.

### Expectation

Use large language models for time series forecasting.

```
prompt -> time series values
model -> any huggingface model
output -> forecasted time series
```



Discussion / hints:

Fix patch:
diff --git a/MANIFEST.in b/MANIFEST.in
index 469520f..cdebd58 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -4,6 +4,8 @@ include HISTORY.md
 include LICENSE
 include README.md
 
+recursive-include sigllm *.json
+
 recursive-include tests *
 recursive-exclude * __pycache__
 recursive-exclude * *.py[co]
diff --git a/docs/conf.py b/docs/conf.py
index 5407d73..2b1e375 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -31,7 +31,7 @@
 # Add any Sphinx extension module names here, as strings. They can be
 # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
 extensions = [
-    'm2r',
+    'm2r2',
     'sphinx.ext.autodoc',
     'sphinx.ext.githubpages',
     'sphinx.ext.viewcode',
diff --git a/setup.py b/setup.py
index 6540fd6..baff6ff 100644
--- a/setup.py
+++ b/setup.py
@@ -12,8 +12,16 @@
     history = history_file.read()
 
 install_requires = [
-    'numpy', 'openai', 'pandas','orion', 'matplotlib', 'scikit-learn',
+    'numpy',
+    'openai',
+    'pandas',
+    'orion-ml',
+    'matplotlib',
+    'scikit-learn',
     'tiktoken',
+    'transformers',
+    'torch',
+    'accelerate'
 ]
 
 setup_requires = [
@@ -23,7 +31,7 @@
 tests_require = [
     'pytest>=3.4.2',
     'pytest-cov>=2.6.0',
-    'rundoc>=0.4.3',
+    'rundoc>=0.4.3,<0.5',
 ]
 
 development_requires = [
@@ -33,26 +41,27 @@
     'watchdog>=0.8.3',
 
     # docs
-    'm2r>=0.2.0,<0.3',
-    'Sphinx>=1.7.1,<3',
+    'm2r2>=0.2.5,<0.3',
+    'Sphinx>=3,<3.3',
     'sphinx_rtd_theme>=0.2.4,<0.5',
     'autodocsumm>=0.1.10',
 
     # style check
-    'flake8>=3.7.7',
-    'isort>=4.3.4',
+    'flake8>=3.7.7,<4',
+    'isort>=4.3.4,<5',
 
     # fix style issues
-    'autoflake>=1.2',
-    'autopep8>=1.4.3',
+    'autoflake>=1.2,<2',
+    'autopep8>=1.4.3,<2',
+    'importlib-metadata<5',
 
     # distribute on PyPI
-    'twine>=1.10.0',
+    'twine>=1.10.0,<4',
     'wheel>=0.30.0',
 
     # Advanced testing
-    'coverage>=4.5.1',
-    'tox>=2.9.1',
+    'coverage>=4.5.1,<6',
+    'tox>=2.9.1,<4',
     'invoke',
 ]
 
diff --git a/sigllm/forecasting/__init__.py b/sigllm/forecasting/__init__.py
new file mode 100644
index 0000000..527c6d5
--- /dev/null
+++ b/sigllm/forecasting/__init__.py
@@ -0,0 +1,9 @@
+from sigllm.forecasting.gpt import GPT
+from sigllm.forecasting.huggingface import HF
+from sigllm.forecasting.preprocessing import Signal2String
+
+__all__ = (
+    'GPT',
+    'HF',
+    'Signal2String'
+)
diff --git a/sigllm/forecasting/gpt.py b/sigllm/forecasting/gpt.py
new file mode 100644
index 0000000..6f14725
--- /dev/null
+++ b/sigllm/forecasting/gpt.py
@@ -0,0 +1,119 @@
+# -*- coding: utf-8 -*-
+
+import json
+import os
+
+import openai
+import tiktoken
+
+PROMPT_PATH = os.path.join(
+    os.path.dirname(os.path.abspath(__file__)),
+    'gpt_messages.json'
+)
+
+PROMPTS = json.load(open(PROMPT_PATH))
+
+VALID_NUMBERS = list("0123456789 ")
+BIAS = 30
+
+
+class GPT:
+    """Prompt GPT models to forecast a time series.
+
+    Args:
+        name (str):
+            Model name. Default to `'gpt-3.5-turbo'`.
+        chat (bool):
+            Whether you're using a chat model or not. Default to `True`.
+        sep (str):
+            String to separate each element in values. Default to `','`.
+    """
+
+    def __init__(self, name='gpt-3.5-turbo', chat=True, sep=','):
+        self.name = name
+        self.chat = chat
+        self.sep = sep
+
+        self.tokenizer = tiktoken.encoding_for_model(self.name)
+
+        valid_tokens = []
+        for number in VALID_NUMBERS:
+            token = self.tokenizer.encode(number)
+            valid_tokens.append(token)
+
+        valid_tokens.append(self.tokenizer.encode(self.sep))
+        self.logit_bias = {token: BIAS for token in valid_tokens}
+
+    def forecast(self, text, steps=1, temp=1, top_p=1, logprobs=False, top_logprobs=None,
+                 samples=1, seed=None):
+        """Use GPT to forecast a signal.
+
+        Args:
+            text (str):
+                A string containing signal values.
+            steps (int):
+                Number of steps ahead to forecast. Default `1`.
+            temp (float):
+                Sampling temperature to use, between 0 and 2. Higher values like 0.8 will
+                make the output more random, while lower values like 0.2 will make it
+                more focused and deterministic. Do not use with `top_p`. Default to `1`.
+            top_p (float):
+                Alternative to sampling with temperature, called nucleus sampling, where the
+                model considers the results of the tokens with top_p probability mass.
+                So 0.1 means only the tokens comprising the top 10% probability mass are
+                considered. Do not use with `temp`. Default to `1`.
+            logprobs (bool):
+                Whether to return the log probabilities of the output tokens or not.
+                Defaults to `False`.
+            top_logprobs (int):
+                An integer between 0 and 20 specifying the number of most likely tokens
+                to return at each token position. Default to `None`.
+            samples (int):
+                Number of forecasts to generate for each input message. Default to `1`.
+            seed (int):
+                Beta feature by OpenAI to sample deterministically. Default to `None`.
+
+        Returns:
+            list, list:
+                * List of forecasted signal values.
+                * Optionally, a list of the output tokens' log probabilities.
+        """
+        input_length = len(self.tokenizer.encode(text))
+        average_length = (input_length + 1) // len(text.split(','))
+        max_tokens = average_length * steps
+
+        if self.chat:
+            message = ' '.join(PROMPTS['user_message'], text, self.sep)
+            response = openai.ChatCompletion.create(
+                model=self.name,
+                messages=[
+                    {"role": "system", "content": PROMPTS['system_message']},
+                    {"role": "user", "content": message}
+                ],
+                max_tokens=max_tokens,
+                temperature=temp,
+                logprobs=logprobs,
+                top_logprobs=top_logprobs,
+                n=samples,
+            )
+            responses = [choice.message.content for choice in response.choices]
+
+        else:
+            message = ' '.join(text, self.sep)
+            response = openai.Completion.create(
+                model=self.name,
+                prompt=message,
+                max_tokens=max_tokens,
+                temperature=temp,
+                logprobs=logprobs,
+                top_logprobs=top_logprobs,
+                logit_bias=self.logit_bias,
+                n=samples
+            )
+            responses = [choice.text for choice in response.choices]
+
+        if logprobs:
+            probs = [choice.logprobs for choice in response.choices]
+            return responses, probs
+
+        return responses
diff --git a/sigllm/forecasting/gpt_messages.json b/sigllm/forecasting/gpt_messages.json
new file mode 100644
index 0000000..9238be4
--- /dev/null
+++ b/sigllm/forecasting/gpt_messages.json
@@ -0,0 +1,5 @@
+{
+    "system_message": "You are a helpful assistant that performs time series predictions. The user will provide a sequence and you will predict the remaining sequence. The sequence is represented by decimal strings separated by commas.",
+    "user_message": "Please continue the following sequence without producing any additional text. Do not say anything like 'the next terms in the sequence are', just return the numbers. Sequence:\n",
+    "citation": "https://arxiv.org/pdf/2310.07820.pdf"
+}
\ No newline at end of file
diff --git a/sigllm/forecasting/huggingface.py b/sigllm/forecasting/huggingface.py
new file mode 100644
index 0000000..fcc3db6
--- /dev/null
+++ b/sigllm/forecasting/huggingface.py
@@ -0,0 +1,124 @@
+# -*- coding: utf-8 -*-
+
+import logging
+
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+LOGGER = logging.getLogger(__name__)
+
+DEFAULT_BOS_TOKEN = "
"
+DEFAULT_EOS_TOKEN = "
"
+DEFAULT_UNK_TOKEN = "<unk>"
+DEFAULT_PAD_TOKEN = "<pad>"
+
+VALID_NUMBERS = list("0123456789")
+
+DEFAULT_MODEL = 'mistralai/Mistral-7B-Instruct-v0.2'
+
+
+class HF:
+    """Prompt Pretrained models on HuggingFace to forecast a time series.
+
+    Args:
+        name (str):
+            Model name. Default to `'mistralai/Mistral-7B-Instruct-v0.2'`.
+        sep (str):
+            String to separate each element in values. Default to `','`.
+    """
+
+    def __init__(self, name=DEFAULT_MODEL, sep=','):
+        self.name = name
+        self.sep = sep
+
+        self.tokenizer = AutoTokenizer.from_pretrained(self.name, use_fast=False)
+
+        # special tokens
+        special_tokens_dict = dict()
+        if self.tokenizer.eos_token is None:
+            special_tokens_dict["eos_token"] = DEFAULT_EOS_TOKEN
+        if self.tokenizer.bos_token is None:
+            special_tokens_dict["bos_token"] = DEFAULT_BOS_TOKEN
+        if self.tokenizer.unk_token is None:
+            special_tokens_dict["unk_token"] = DEFAULT_UNK_TOKEN
+        if self.tokenizer.pad_token is None:
+            special_tokens_dict["pad_token"] = DEFAULT_PAD_TOKEN
+
+        self.tokenizer.add_special_tokens(special_tokens_dict)
+        self.tokenizer.pad_token = self.tokenizer.eos_token  # indicate the end of the time series
+
+        # invalid tokens
+        valid_tokens = []
+        for number in VALID_NUMBERS:
+            token = self.tokenizer.convert_tokens_to_ids(number)
+            valid_tokens.append(token)
+
+        valid_tokens.append(self.tokenizer.convert_tokens_to_ids(self.sep))
+        self.invalid_tokens = [[i]
+                               for i in range(len(self.tokenizer) - 1) if i not in valid_tokens]
+
+        self.model = AutoModelForCausalLM.from_pretrained(
+            self.name,
+            device_map="auto",
+            torch_dtype=torch.float16,
+        )
+
+        self.model.eval()
+
+    def forecast(self, text, steps=1, temp=1, top_p=1, raw=False, samples=1, padding=0):
+        """Use GPT to forecast a signal.
+
+        Args:
+            text (str):
+                A string containing signal values.
+            steps (int):
+                Number of steps ahead to forecast. Default `1`.
+            temp (float):
+                The value used to modulate the next token probabilities. Default to `1`.
+            top_p (float):
+                 If set to float < 1, only the smallest set of most probable tokens with
+                 probabilities that add up to `top_p` or higher are kept for generation.
+                 Default to `1`.
+            raw (bool):
+                Whether to return the raw output or not. Defaults to `False`.
+            samples (int):
+                Number of forecasts to generate for each input message. Default to `1`.
+            padding (int):
+                Additional padding token to forecast to reduce short horizon predictions.
+                Default to `0`.
+
+        Returns:
+            list, list:
+                * List of forecasted signal values.
+                * Optionally, a list of dictionaries for raw output.
+        """
+        tokenized_input = self.tokenizer(
+            [text],
+            return_tensors="pt"
+        ).to("cuda")
+
+        input_length = tokenized_input['input_ids'].shape[1]
+        average_length = input_length / len(text.split(','))
+        max_tokens = (average_length + padding) * steps
+
+        generate_ids = self.model.generate(
+            **tokenized_input,
+            do_sample=True,
+            max_new_tokens=max_tokens,
+            temperature=temp,
+            top_p=top_p,
+            bad_words_ids=self.invalid_tokens,
+            renormalize_logits=True,
+            num_return_sequences=samples
+        )
+
+        responses = self.tokenizer.batch_decode(
+            generate_ids[:, input_length:],
+            skip_special_tokens=True,
+            clean_up_tokenization_spaces=False
+        )
+
+        if raw:
+            return responses, generate_ids
+
+        return responses
diff --git a/sigllm/forecasting/preprocessing.py b/sigllm/forecasting/preprocessing.py
new file mode 100644
index 0000000..b476f57
--- /dev/null
+++ b/sigllm/forecasting/preprocessing.py
@@ -0,0 +1,83 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+"""
+Preprocessing module for time series forecasting.
+"""
+
+import numpy as np
+
+
+class Signal2String:
+    """Convert a signal into a string.
+
+    Prepare a univariate time series signal for LLMs.
+    Transforms a float array into a string of integers.
+
+    Args:
+        sep (str):
+            String to separate each element in values. Default to `','`.
+        space (bool):
+            Whether to add space between each digit in the result. Default to `False`.
+        decimal (int):
+            Number of decimal points to keep from the float representation. Default to `0`.
+        rescale(bool):
+            Whether to rescale the time series. Default to `False`.
+    """
+
+    def __init__(self, sep=',', space=False, decimal=0, rescale=False):
+        self.sep = sep
+        self.space = space
+        self.decimal = decimal
+        self.rescale = rescale
+
+    def transform(self, values):
+        """Convert a signal to a string.
+
+        Convert a 1-dimensional time series into text by casting and rescaling it
+        to nonnegative integer values then into a string.
+
+        Args:
+            values (numpy.ndarray):
+                A sequence of signal values.
+
+        Returns:
+            str:
+                Text containing the elements of `values`.
+        """
+        sign = 1 * (values >= 0) - 1 * (values < 0)
+        values = np.abs(values)
+
+        sequence = sign * (values * 10**self.decimal).astype(int)
+
+        # rescale all elements to be nonnegative
+        if self.rescale:
+            sequence = sequence - min(sequence)
+
+        res = self.sep.join(list(map(str, sequence)))
+        if self.space:
+            res = ' '.join(res)
+
+        return res
+
+    def reverse_transform(self, text, trunc=None):
+        """Convert a text string to a signal.
+
+        Convert a string containing digits into an array of numbers.
+
+        Args:
+            text (str):
+                A string containing signal values.
+            trunc (int):
+                Whether to truncate the text to a specific length. Default `None`.
+
+        Returns:
+            numpy.ndarray:
+                A 1-dimensional array containing parsed elements in `text`.
+        """
+        values = list(filter(None, text.split(self.sep)))
+        if trunc:
+            values = values[:trunc]
+
+        values = np.array(list(map(float, values)))
+        return values * 10**(-self.decimal)
diff --git a/tutorials/HFPipeline-S-1.ipynb b/tutorials/HFPipeline-S-1.ipynb
new file mode 100644
index 0000000..5548ff7
--- /dev/null
+++ b/tutorials/HFPipeline-S-1.ipynb
@@ -0,0 +1,513 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "f7300691-9931-45c8-b8a0-b0bc36a797c3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "from tqdm import tqdm\n",
+    "\n",
+    "from sklearn.preprocessing import MinMaxScaler\n",
+    "from orion.data import load_signal, load_anomalies\n",
+    "from mlstars.custom.timeseries_preprocessing import rolling_window_sequences\n",
+    "\n",
+    "from sigllm.forecasting import Signal2String, HF"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "98a74d37-d0f3-4970-a3eb-e30ea578dc11",
+   "metadata": {},
+   "source": [
+    "# Load Time Series"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "221d0cd7-82d6-41d9-9a7d-4e8422b0e5dc",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "signal_name = 'S-1'\n",
+    "\n",
+    "df = load_signal(signal_name)[:200]\n",
+    "\n",
+    "t, timeseries = df.T.values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "e52fbaae-dff4-4573-9eb9-23121a1e38d5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "plt.plot(t, timeseries);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "f3b9051f-94f3-466c-8b35-bc08191768af",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# helper plotting function\n",
+    "\n",
+    "def plot_results(x, title=None):\n",
+    "    median = np.median(x, axis=0)\n",
+    "    lower = np.quantile(x, 0.05, axis=0)\n",
+    "    upper = np.quantile(x, 0.95, axis=0)\n",
+    "    \n",
+    "    plt.plot(t[:stop], train)\n",
+    "    plt.plot(t[stop:], test, color='green', label='true')\n",
+    "    \n",
+    "    plt.plot(t[stop:], median, color='purple', label='pred');\n",
+    "    plt.fill_between(t[stop:], lower, upper, alpha=0.3, color='purple')\n",
+    "\n",
+    "    if title:\n",
+    "        plt.title(title)\n",
+    "    \n",
+    "    plt.legend();"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "3b1d7ad5-3db4-4d47-bd70-72c6267a0ad7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# split time series\n",
+    "\n",
+    "stop = int(np.ceil(0.7 * len(timeseries)))\n",
+    "\n",
+    "train, test = timeseries[:stop], timeseries[stop:]\n",
+    "\n",
+    "plt.plot(t[:stop], train)\n",
+    "plt.plot(t[stop:], test);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "56c314c3-fe3e-4b54-929f-bdf30c715dbb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "converter = Signal2String(decimal=0, sep=',', space=False)\n",
+    "\n",
+    "train_str = converter.transform(train) ## TODO: add seperator to the end and remove it from gpt.py"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "40fdf8ad-9e85-48a9-858d-25844fa66549",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "ba6c8a565c224a1fb6bfe1ed5d212c22",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Loading checkpoint shards:   0%|          | 0/3 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "model_name = 'mistralai/Mistral-7B-Instruct-v0.2'\n",
+    "\n",
+    "model = HF(model_name, converter.sep)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "146922e3-77cf-4160-ae7c-add0e2f9c113",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      "2024-04-05 16:58:57.582653: E tensorflow/compiler/xla/stream_executor/cuda/cuda_dnn.cc:9342] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
+      "2024-04-05 16:58:57.582692: E tensorflow/compiler/xla/stream_executor/cuda/cuda_fft.cc:609] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
+      "2024-04-05 16:58:57.582713: E tensorflow/compiler/xla/stream_executor/cuda/cuda_blas.cc:1518] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
+      "2024-04-05 16:58:57.588572: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+      "To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
+      "2024-04-05 16:58:58.258996: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
+     ]
+    }
+   ],
+   "source": [
+    "output = model.forecast(train_str, steps=len(test), samples=10, padding=1) ## TODO: fix length error"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "b296efd7-a3db-462f-a5b7-577a6b80df47",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Recorded 0 incomplete forecasts\n"
+     ]
+    }
+   ],
+   "source": [
+    "predictions = []\n",
+    "incomplete = 0\n",
+    "for o in output:\n",
+    "    pred = converter.reverse_transform(o, trunc=len(test))\n",
+    "    if len(pred) != len(test):\n",
+    "        incomplete += 1\n",
+    "        continue\n",
+    "\n",
+    "    predictions.append(pred)\n",
+    "\n",
+    "print(f\"Recorded {incomplete} incomplete forecasts\")\n",
+    "predictions = np.array(predictions)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "61a72f8a-9f0d-46a8-be12-4adbf60993bb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_results(predictions, title='mistral test')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6909acb9-ecac-4bb6-b342-d32e6121b21b",
+   "metadata": {},
+   "source": [
+    "# Run Model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "ea32ba4a-55f1-4ee0-b045-a8b3d97129d3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# helper plotting function\n",
+    "\n",
+    "def plot_results_windows(x, title=None):\n",
+    "    median = np.median(x.T, axis=0)\n",
+    "    lower = np.quantile(x.T, 0.05, axis=0)\n",
+    "    upper = np.quantile(x.T, 0.95, axis=0)\n",
+    "    \n",
+    "    plt.plot(t, timeseries)\n",
+    "    plt.plot(y_index, y, color='green', label='true')\n",
+    "    \n",
+    "    plt.plot(y_index, median, color='purple', label='pred');\n",
+    "    plt.fill_between(y_index, lower, upper, alpha=0.3, color='purple')\n",
+    "\n",
+    "    if title:\n",
+    "        plt.title(title)\n",
+    "    \n",
+    "    plt.legend();"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "86299230-0a58-4e0b-954e-75d3936f6092",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# scaler \n",
+    "\n",
+    "scaler = MinMaxScaler(feature_range=(0, 1))\n",
+    "timeseries = scaler.fit_transform(timeseries.reshape(-1, 1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "e149eea9-c28c-4ff3-a355-36a1ff29deb9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# make rolling windows\n",
+    "\n",
+    "window_size = 140\n",
+    "step_size = 1\n",
+    "X, y, X_index, y_index = rolling_window_sequences(\n",
+    "    timeseries, t, \n",
+    "    target_column=0, \n",
+    "    target_size=1, \n",
+    "    window_size=window_size, \n",
+    "    step_size=step_size\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "bb9685ff-f051-4a9f-96b7-529a9dc00336",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "392d95e5305446c2b5a2303f56153a2a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Loading checkpoint shards:   0%|          | 0/3 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING:root:Some parameters are on the meta device device because they were offloaded to the cpu.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# initialization\n",
+    "\n",
+    "converter = Signal2String(decimal=2, sep=',', space=False, rescale=False)\n",
+    "model_name = 'mistralai/Mistral-7B-Instruct-v0.2'\n",
+    "model = HF(model_name, converter.sep)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "b2f547ef-1b43-4395-add2-e2549185be5f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
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+      " 98%|█████████▊| 59/60 [02:51<00:02,  2.93s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      "100%|██████████| 60/60 [02:54<00:00,  2.91s/it]\n"
+     ]
+    }
+   ],
+   "source": [
+    "results = []\n",
+    "\n",
+    "steps = 10\n",
+    "\n",
+    "for window in tqdm(X):\n",
+    "    input_str = converter.transform(window.flatten())\n",
+    "    output = model.forecast(input_str, steps=steps, samples=5, padding=1)\n",
+    "    results.append(output)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "6a7c6fbb-9d72-43ce-b2b4-2196c4cb2003",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 60/60 [00:00<00:00, 18012.90it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Recorded 0 incomplete forecasts\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "predictions = []\n",
+    "incomplete = 0\n",
+    "for output in tqdm(results):\n",
+    "    result = []\n",
+    "    for o in output:\n",
+    "        pred = converter.reverse_transform(o, trunc=1)\n",
+    "        if len(pred) != 1:\n",
+    "            incomplete += 1\n",
+    "            continue\n",
+    "            \n",
+    "        result.append(pred)\n",
+    "    predictions.append(result)\n",
+    "        \n",
+    "\n",
+    "print(f\"Recorded {incomplete} incomplete forecasts\")\n",
+    "predictions = np.array(predictions)\n",
+    "predictions = predictions[:, :, 0]\n",
+    "\n",
+    "predictions[predictions > 2] = predictions.mean()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "0af87b01-a9ad-4eb8-8703-14d2b58df35c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_results_windows(predictions, title='Mistral Windows, step=5')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.14"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tutorials/HFPipeline.ipynb b/tutorials/HFPipeline.ipynb
new file mode 100644
index 0000000..42ce204
--- /dev/null
+++ b/tutorials/HFPipeline.ipynb
@@ -0,0 +1,499 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "f7300691-9931-45c8-b8a0-b0bc36a797c3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "from tqdm import tqdm\n",
+    "\n",
+    "from mlstars.custom.timeseries_preprocessing import rolling_window_sequences\n",
+    "from sigllm.forecasting import Signal2String, HF"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "98a74d37-d0f3-4970-a3eb-e30ea578dc11",
+   "metadata": {},
+   "source": [
+    "# Generage Time Series"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "e52fbaae-dff4-4573-9eb9-23121a1e38d5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "t = list(range(0, 200))\n",
+    "\n",
+    "timeseries = []\n",
+    "for x in t:\n",
+    "    res = x * np.sin(x) + x * np.cos(x) + 5*x\n",
+    "    timeseries.append(res)\n",
+    "\n",
+    "timeseries = np.array(timeseries)\n",
+    "plt.plot(t, timeseries);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a1be8f93-1f69-48a7-91cc-f7070f355a40",
+   "metadata": {},
+   "source": [
+    "# Single Forecast"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "f3b9051f-94f3-466c-8b35-bc08191768af",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# helper plotting function\n",
+    "\n",
+    "def plot_results(x, title=None):\n",
+    "    median = np.median(x, axis=0)\n",
+    "    lower = np.quantile(x, 0.05, axis=0)\n",
+    "    upper = np.quantile(x, 0.95, axis=0)\n",
+    "    \n",
+    "    plt.plot(t[:stop], train)\n",
+    "    plt.plot(t[stop:], test, color='green', label='true')\n",
+    "    \n",
+    "    plt.plot(t[stop:], median, color='purple', label='pred');\n",
+    "    plt.fill_between(t[stop:], lower, upper, alpha=0.3, color='purple')\n",
+    "\n",
+    "    if title:\n",
+    "        plt.title(title)\n",
+    "    \n",
+    "    plt.legend();"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "3b1d7ad5-3db4-4d47-bd70-72c6267a0ad7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# split time series\n",
+    "\n",
+    "stop = int(np.ceil(0.7 * len(timeseries)))\n",
+    "\n",
+    "train, test = timeseries[:stop], timeseries[stop:]\n",
+    "\n",
+    "plt.plot(t[:stop], train)\n",
+    "plt.plot(t[stop:], test);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "56c314c3-fe3e-4b54-929f-bdf30c715dbb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "converter = Signal2String(decimal=0, sep=',', space=False)\n",
+    "\n",
+    "train_str = converter.transform(train) ## TODO: add seperator to the end and remove it from gpt.py"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "40fdf8ad-9e85-48a9-858d-25844fa66549",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6a4d9bc89e384af595075d060ca69376",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Loading checkpoint shards:   0%|          | 0/3 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "model_name = 'mistralai/Mistral-7B-Instruct-v0.2'\n",
+    "\n",
+    "model = HF(model_name, converter.sep)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "146922e3-77cf-4160-ae7c-add0e2f9c113",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n"
+     ]
+    }
+   ],
+   "source": [
+    "output = model.forecast(train_str, steps=len(test), samples=10, padding=1) ## TODO: fix length error"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "b296efd7-a3db-462f-a5b7-577a6b80df47",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Recorded 1 incomplete forecasts\n"
+     ]
+    }
+   ],
+   "source": [
+    "predictions = []\n",
+    "incomplete = 0\n",
+    "for o in output:\n",
+    "    pred = converter.reverse_transform(o, trunc=len(test))\n",
+    "    if len(pred) != len(test):\n",
+    "        incomplete += 1\n",
+    "        continue\n",
+    "\n",
+    "    predictions.append(pred)\n",
+    "\n",
+    "print(f\"Recorded {incomplete} incomplete forecasts\")\n",
+    "predictions = np.array(predictions)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "61a72f8a-9f0d-46a8-be12-4adbf60993bb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_results(predictions, title='mistral test')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6909acb9-ecac-4bb6-b342-d32e6121b21b",
+   "metadata": {},
+   "source": [
+    "# Multiple Window Forecasting"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "ea32ba4a-55f1-4ee0-b045-a8b3d97129d3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# helper plotting function\n",
+    "\n",
+    "def plot_results_windows(x, title=None):\n",
+    "    median = np.median(x.T, axis=0)\n",
+    "    lower = np.quantile(x.T, 0.05, axis=0)\n",
+    "    upper = np.quantile(x.T, 0.95, axis=0)\n",
+    "    \n",
+    "    plt.plot(t, timeseries)\n",
+    "    plt.plot(y_index, y, color='green', label='true')\n",
+    "    \n",
+    "    plt.plot(y_index, median, color='purple', label='pred');\n",
+    "    plt.fill_between(y_index, lower, upper, alpha=0.3, color='purple')\n",
+    "\n",
+    "    if title:\n",
+    "        plt.title(title)\n",
+    "    \n",
+    "    plt.legend();"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "e149eea9-c28c-4ff3-a355-36a1ff29deb9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# make rolling windows\n",
+    "\n",
+    "window_size = 140\n",
+    "step_size = 1\n",
+    "X, y, X_index, y_index = rolling_window_sequences(\n",
+    "    timeseries.reshape(-1, 1), t, \n",
+    "    target_column=0, \n",
+    "    target_size=1, \n",
+    "    window_size=window_size, \n",
+    "    step_size=step_size\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "bb9685ff-f051-4a9f-96b7-529a9dc00336",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/smish/miniconda/envs/nlp/lib/python3.10/site-packages/accelerate/utils/modeling.py:1341: UserWarning: Current model requires 402656256 bytes of buffer for offloaded layers, which seems does not fit any GPU's remaining memory. If you are experiencing a OOM later, please consider using offload_buffers=True.\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e078143bc9e240b1a1681ada148941a6",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Loading checkpoint shards:   0%|          | 0/3 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "WARNING:root:Some parameters are on the meta device device because they were offloaded to the cpu.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# initialization\n",
+    "\n",
+    "converter = Signal2String(decimal=0, sep=',', space=False)\n",
+    "model_name = 'mistralai/Mistral-7B-Instruct-v0.2'\n",
+    "model = HF(model_name, converter.sep)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "b2f547ef-1b43-4395-add2-e2549185be5f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "  0%|          | 0/60 [00:00<?, ?it/s]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      "  2%|▏         | 1/60 [01:05<1:03:59, 65.08s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      "  3%|▎         | 2/60 [02:10<1:02:53, 65.06s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      "  5%|▌         | 3/60 [03:15<1:01:49, 65.09s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      "  7%|▋         | 4/60 [04:20<1:00:45, 65.10s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      "  8%|▊         | 5/60 [05:25<59:40, 65.09s/it]  Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 10%|█         | 6/60 [06:30<58:35, 65.10s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 12%|█▏        | 7/60 [07:35<57:29, 65.08s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 13%|█▎        | 8/60 [08:42<56:46, 65.51s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 15%|█▌        | 9/60 [09:48<55:58, 65.84s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 18%|█▊        | 11/60 [12:03<54:36, 66.86s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 20%|██        | 12/60 [13:12<53:56, 67.43s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 22%|██▏       | 13/60 [14:21<53:07, 67.83s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 23%|██▎       | 14/60 [15:29<52:12, 68.09s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 25%|██▌       | 15/60 [16:38<51:13, 68.29s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 27%|██▋       | 16/60 [17:47<50:09, 68.41s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 28%|██▊       | 17/60 [18:56<49:06, 68.52s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 30%|███       | 18/60 [20:04<48:00, 68.59s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 32%|███▏      | 19/60 [21:13<46:54, 68.64s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 33%|███▎      | 20/60 [22:22<45:46, 68.67s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 35%|███▌      | 21/60 [23:31<44:39, 68.71s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 37%|███▋      | 22/60 [24:40<43:31, 68.73s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 38%|███▊      | 23/60 [25:48<42:23, 68.74s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 40%|████      | 24/60 [26:58<41:29, 69.15s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 42%|████▏     | 25/60 [28:09<40:30, 69.45s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 43%|████▎     | 26/60 [29:19<39:27, 69.64s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 45%|████▌     | 27/60 [30:29<38:23, 69.79s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 47%|████▋     | 28/60 [31:39<37:16, 69.88s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 48%|████▊     | 29/60 [32:47<35:53, 69.46s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 50%|█████     | 30/60 [33:55<34:28, 68.95s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 52%|█████▏    | 31/60 [35:03<33:09, 68.60s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 53%|█████▎    | 32/60 [36:11<31:54, 68.39s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 55%|█████▌    | 33/60 [37:19<30:48, 68.47s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 57%|█████▋    | 34/60 [38:29<29:45, 68.68s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 58%|█████▊    | 35/60 [39:36<28:31, 68.45s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 60%|██████    | 36/60 [40:44<27:18, 68.27s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 62%|██████▏   | 37/60 [41:52<26:07, 68.16s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 63%|██████▎   | 38/60 [43:02<25:10, 68.65s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 65%|██████▌   | 39/60 [44:10<23:56, 68.42s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 67%|██████▋   | 40/60 [45:18<22:44, 68.25s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 68%|██████▊   | 41/60 [46:26<21:34, 68.14s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 70%|███████   | 42/60 [47:34<20:25, 68.06s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 72%|███████▏  | 43/60 [48:41<19:16, 68.02s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 73%|███████▎  | 44/60 [49:49<18:07, 67.98s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 75%|███████▌  | 45/60 [50:57<16:59, 67.95s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 77%|███████▋  | 46/60 [52:05<15:51, 67.93s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 78%|███████▊  | 47/60 [53:13<14:43, 67.93s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 80%|████████  | 48/60 [54:21<13:35, 67.92s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 82%|████████▏ | 49/60 [55:29<12:27, 67.91s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 83%|████████▎ | 50/60 [56:37<11:19, 67.93s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 85%|████████▌ | 51/60 [57:45<10:11, 67.93s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 87%|████████▋ | 52/60 [58:53<09:03, 67.92s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 88%|████████▊ | 53/60 [1:00:01<07:55, 67.92s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 90%|█████████ | 54/60 [1:01:08<06:47, 67.92s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 92%|█████████▏| 55/60 [1:02:16<05:39, 67.91s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 93%|█████████▎| 56/60 [1:03:24<04:31, 67.91s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 95%|█████████▌| 57/60 [1:04:32<03:23, 67.91s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 97%|█████████▋| 58/60 [1:05:41<02:16, 68.30s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      " 98%|█████████▊| 59/60 [1:06:51<01:08, 68.57s/it]Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.\n",
+      "100%|██████████| 60/60 [1:08:00<00:00, 68.00s/it]\n"
+     ]
+    }
+   ],
+   "source": [
+    "results = []\n",
+    "\n",
+    "steps = 10\n",
+    "\n",
+    "for window in tqdm(X):\n",
+    "    input_str = converter.transform(window.flatten())\n",
+    "    output = model.forecast(input_str, steps=steps, samples=5, padding=1)\n",
+    "    results.append(output)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "6a7c6fbb-9d72-43ce-b2b4-2196c4cb2003",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 60/60 [00:00<00:00, 17290.16it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Recorded 0 incomplete forecasts\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "predictions = []\n",
+    "incomplete = 0\n",
+    "for output in tqdm(results):\n",
+    "    result = []\n",
+    "    for o in output:\n",
+    "        pred = converter.reverse_transform(o, trunc=1)\n",
+    "        if len(pred) != 1:\n",
+    "            incomplete += 1\n",
+    "            continue\n",
+    "            \n",
+    "        result.append(pred)\n",
+    "    predictions.append(result)\n",
+    "        \n",
+    "\n",
+    "print(f\"Recorded {incomplete} incomplete forecasts\")\n",
+    "predictions = np.array(predictions)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "0af87b01-a9ad-4eb8-8703-14d2b58df35c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "predictions = predictions[:, :, 0]\n",
+    "\n",
+    "plot_results_windows(predictions, title='Mistral Windows, step=5')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.14"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tutorials/benchmark.py b/tutorials/benchmark.py
new file mode 100644
index 0000000..71090fe
--- /dev/null
+++ b/tutorials/benchmark.py
@@ -0,0 +1,193 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+import ast
+import os
+import logging
+import warnings
+import pickle
+from datetime import datetime
+from functools import partial
+from glob import glob
+
+import pandas as pd
+import numpy as np
+from tqdm import tqdm
+from sklearn.preprocessing import MinMaxScaler
+from mlstars.custom.timeseries_preprocessing import rolling_window_sequences
+from orion.data import load_signal, load_anomalies
+from orion.primitives.timeseries_errors import regression_errors
+from orion.primitives.timeseries_anomalies import find_anomalies
+from orion.evaluation import CONTEXTUAL_METRICS as METRICS
+from orion.evaluation import contextual_confusion_matrix
+from orion.benchmark import _parse_confusion_matrix, _load_signal
+
+from sigllm.forecasting import Signal2String, HF
+
+
+warnings.simplefilter('ignore')
+
+LOGGER = logging.getLogger(__name__)
+
+BUCKET = 'sintel-orion-benchmark'
+S3_URL = 'https://{}.s3.amazonaws.com/{}'
+
+BENCHMARK_DATA = pd.read_csv(S3_URL.format(
+    BUCKET, 'datasets.csv'), index_col=0, header=None).applymap(ast.literal_eval).to_dict()[1]
+
+BENCHMARK_PATH = os.path.join(
+    os.path.dirname(os.path.abspath('')),
+    'benchmark'
+)
+
+os.makedirs(BENCHMARK_PATH, exist_ok=True)
+
+DONE = glob(BENCHMARK_PATH + '*.csv')
+
+BENCHMARK_DATA = {
+    "artificialWithAnomaly": BENCHMARK_DATA["artificialWithAnomaly"],
+    "realAWSCloudwatch": BENCHMARK_DATA["realAWSCloudwatch"]
+}
+
+test_split = False
+MAX = 2
+
+
+del METRICS['accuracy']
+METRICS['confusion_matrix'] = contextual_confusion_matrix
+metrics = {k: partial(fun, weighted=False) for k, fun in METRICS.items()}
+
+# setup
+
+# rolling windows settings
+window_size = 140
+step_size = 1
+
+# signal to string converter settings
+decimals = 2
+seperator = ','
+space = False
+rescale = True
+
+# HF model settings
+model_name = 'mistralai/Mistral-7B-Instruct-v0.2'
+name_to_keep = model_name.split('/')[-1]
+steps = 10
+samples = 10
+padding = 1
+temp = 0.9
+
+# initialization
+
+scaler = MinMaxScaler(feature_range=(0, 1))
+converter = Signal2String(decimal=decimals, sep=seperator, space=space, rescale=rescale)
+model = HF(model_name, converter.sep)
+
+
+# make rolling windows
+
+def run_experiment(signal_name):
+    file_name = os.path.join(BENCHMARK_PATH, f'{name_to_keep}_{signal}_{dataset}_{temp}_{samples}')
+    
+    data = load_signal(signal_name)
+    truth = load_anomalies(signal_name)
+    train, test = _load_signal(signal_name, test_split)
+
+    timestamps, values = data.values.T
+
+    start = datetime.utcnow()
+
+    timeseries = scaler.fit_transform(values.reshape(-1, 1))
+
+    X, y, X_index, y_index = rolling_window_sequences(
+        timeseries, timestamps, 
+        target_column=0, 
+        target_size=1, 
+        window_size=window_size, 
+        step_size=step_size
+    )
+
+    outputs = []
+    for window in tqdm(X):
+        input_str = converter.transform(window.flatten())
+        output = model.forecast(input_str, steps=steps, samples=samples, padding=padding, temp=temp)
+        outputs.append(output)
+
+    with open(file_name + '_raw_forecast.pkl', 'wb') as f:
+        pickle.dump(outputs, f)
+
+    predictions = []
+    incomplete = 0
+
+    for output in outputs:
+        result = []
+        for o in output:
+            try:
+                pred = converter.reverse_transform(o, trunc=1)
+                if len(pred) != 1:
+                    incomplete += 1
+                    continue
+
+            except Exception as ex:
+                LOGGER.exception("Exception reverse transform on signal %s, error %s.", signal_name, ex)
+                pred = None
+                
+            result.append(pred)
+        predictions.append(result)
+        
+    LOGGER.info(f"Recorded {incomplete} incomplete forecasts")
+    predictions = np.array(predictions)
+    predictions = predictions[:, :, 0]
+    predictions[predictions > MAX] = predictions.mean()
+    pred_median = np.median(predictions.T, axis=0)
+
+    errors = regression_errors(y, pred_median)
+    events = find_anomalies(errors, y_index, window_size_portion=0.33, window_step_size_portion=0.1, fixed_threshold=True)
+
+    anomalies = pd.DataFrame(list(events), columns=['start', 'end', 'score'])
+    anomalies['start'] = anomalies['start'].astype('int64')
+    anomalies['end'] = anomalies['end'].astype('int64')
+
+    elapsed = datetime.utcnow() - start
+
+    try:
+        scores = {
+            name: scorer(truth, anomalies, test)
+            for name, scorer in metrics.items()
+        }
+        _parse_confusion_matrix(scores, truth)
+
+        status = 'OK'
+
+    except Exception as ex:
+        LOGGER.exception("Exception scoring signal %s, error %s.", signal_name, ex)
+        
+        scores = {
+            name: 0 for name in metrics.keys()
+        }
+
+        status = 'ERROR'
+
+    scores['status'] = status
+    scores['predictions'] = predictions
+    scores['anomalies'] = anomalies
+    scores['errors'] = errors
+    scores['incomplete'] = incomplete
+    scores['elapsed'] = elapsed.total_seconds()
+
+    record = pd.DataFrame.from_records([scores], columns=scores.keys())
+    record.to_csv(file_name + '_scores.csv', index=False)
+
+
+if __name__ == "__main__":
+    for dataset, signals in BENCHMARK_DATA.items():
+        for i, signal in enumerate(signals):
+            file_name = os.path.join(BENCHMARK_PATH, f'{name_to_keep}_{signal}_{dataset}_{temp}_{samples}')
+            if file_name + '_scores.csv' in DONE:
+                LOGGER.info(f'Skipping {signal}')
+                continue
+
+            LOGGER.info(f'{i}/{len(signals)} Running experiment for {signal}')
+            print(f'{i}/{len(signals)} Running experiment for {signal}')
+            run_experiment(signal)
+


Test patch:
diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
index 94223f8..27b263f 100644
--- a/.github/workflows/tests.yml
+++ b/.github/workflows/tests.yml
@@ -28,22 +28,22 @@ jobs:
       run: invoke lint
 
 
-  docs:
-    runs-on: ${{ matrix.os }}
-    strategy:
-      matrix:
-        python-version: ['3.8', '3.9', '3.10', '3.11']
-        os: [ubuntu-20.04]
-    steps:
-    - uses: actions/checkout@v1
-    - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2
-      with:
-        python-version: ${{ matrix.python-version }}
-    - name: Install package
-      run: pip install .[dev]
-    - name: make docs
-      run: make docs
+  # docs:
+  #   runs-on: ${{ matrix.os }}
+  #   strategy:
+  #     matrix:
+  #       python-version: ['3.8', '3.9', '3.10', '3.11']
+  #       os: [ubuntu-20.04]
+  #   steps:
+  #   - uses: actions/checkout@v1
+  #   - name: Set up Python ${{ matrix.python-version }}
+  #     uses: actions/setup-python@v2
+  #     with:
+  #       python-version: ${{ matrix.python-version }}
+  #   - name: Install package
+  #     run: pip install .[dev]
+  #   - name: make docs
+  #     run: make docs
 
 
   readme:
@@ -82,37 +82,37 @@ jobs:
       run: invoke unit
 
 
-  minimum:
-    runs-on: ${{ matrix.os }}
-    strategy:
-      matrix:
-        python-version: ['3.8', '3.9', '3.10', '3.11']
-        os: [ubuntu-20.04, macos-latest]
-    steps:
-    - uses: actions/checkout@v1
-    - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2
-      with:
-        python-version: ${{ matrix.python-version }}
-    - name: Install package and dependencies
-      run: pip install invoke .[test]
-    - name: invoke minimum
-      run: invoke minimum
+  # minimum:
+  #   runs-on: ${{ matrix.os }}
+  #   strategy:
+  #     matrix:
+  #       python-version: ['3.8', '3.9', '3.10', '3.11']
+  #       os: [ubuntu-20.04, macos-latest]
+  #   steps:
+  #   - uses: actions/checkout@v1
+  #   - name: Set up Python ${{ matrix.python-version }}
+  #     uses: actions/setup-python@v2
+  #     with:
+  #       python-version: ${{ matrix.python-version }}
+  #   - name: Install package and dependencies
+  #     run: pip install invoke .[test]
+  #   - name: invoke minimum
+  #     run: invoke minimum
 
 
-  tutorials:
-    runs-on: ${{ matrix.os }}
-    strategy:
-      matrix:
-        python-version: ['3.8', '3.9', '3.10', '3.11']
-        os: [ubuntu-20.04, macos-latest, windows-latest]
-    steps:
-    - uses: actions/checkout@v1
-    - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2
-      with:
-        python-version: ${{ matrix.python-version }}
-    - name: Install package and dependencies
-      run: pip install invoke jupyter matplotlib .
-    - name: invoke tutorials
-      run: invoke tutorials
\ No newline at end of file
+  # tutorials:
+  #   runs-on: ${{ matrix.os }}
+  #   strategy:
+  #     matrix:
+  #       python-version: ['3.8', '3.9', '3.10', '3.11']
+  #       os: [ubuntu-20.04, macos-latest, windows-latest]
+  #   steps:
+  #   - uses: actions/checkout@v1
+  #   - name: Set up Python ${{ matrix.python-version }}
+  #     uses: actions/setup-python@v2
+  #     with:
+  #       python-version: ${{ matrix.python-version }}
+  #   - name: Install package and dependencies
+  #     run: pip install invoke jupyter matplotlib .
+  #   - name: invoke tutorials
+  #     run: invoke tutorials
\ No newline at end of file
diff --git a/tests/forecasting/test_preprocessing.py b/tests/forecasting/test_preprocessing.py
new file mode 100644
index 0000000..3cd5862
--- /dev/null
+++ b/tests/forecasting/test_preprocessing.py
@@ -0,0 +1,106 @@
+import unittest
+
+import numpy as np
+
+from sigllm.forecasting.preprocessing import Signal2String
+
+
+class Signal2StringTest(unittest.TestCase):
+
+    def test_transform_default(self):
+        converter = Signal2String()
+
+        data = np.array([
+            1, 2, 3, 4, 5
+        ])
+        expected = '1,2,3,4,5'
+
+        output = converter.transform(data)
+
+        assert converter.sep == ','
+        assert converter.space is False
+        assert converter.decimal == 0
+        assert converter.rescale is False
+
+        assert output == expected
+
+    def test_transform_space(self):
+        converter = Signal2String(space=True)
+
+        data = np.array([
+            1, 2, 3, 4, 5
+        ])
+        expected = '1 , 2 , 3 , 4 , 5'
+
+        output = converter.transform(data)
+
+        assert converter.space is True
+        assert output == expected
+
+    def test_transform_sep(self):
+        converter = Signal2String(sep='.')
+
+        data = np.array([
+            1, 2, 3, 4, 5
+        ])
+        expected = '1.2.3.4.5'
+
+        output = converter.transform(data)
+
+        assert converter.sep == '.'
+        assert output == expected
+
+    def test_transform_decimal(self):
+        converter = Signal2String(decimal=2)
+
+        data = np.array([
+            1, 2, 3, 4, 5
+        ])
+        expected = '100,200,300,400,500'
+
+        output = converter.transform(data)
+
+        assert converter.decimal == 2
+        assert output == expected
+
+    def test_transform_rescale(self):
+        converter = Signal2String(rescale=True)
+
+        data = np.array([
+            -1, 2, 3, 4, 5
+        ])
+        expected = '0,3,4,5,6'
+
+        output = converter.transform(data)
+
+        assert converter.rescale is True
+        assert output == expected
+
+    def test_reverse_transform_default(self):
+        converter = Signal2String()
+
+        data = '1,2,3,4,5'
+        expected = np.array([
+            1, 2, 3, 4, 5
+        ])
+
+        output = converter.reverse_transform(data)
+
+        assert converter.sep == ','
+        assert converter.space is False
+        assert converter.decimal == 0
+        assert converter.rescale is False
+
+        np.testing.assert_equal(output, expected)
+
+    def test_transform_reverse_transform(self):
+        converter = Signal2String()
+
+        data = np.array([
+            1, 2, 3, 4, 5
+        ])
+        expected = data
+
+        output = converter.reverse_transform(converter.transform(data))
+
+        np.testing.assert_equal(output, expected)
diff --git a/tests/test_data.py b/tests/test_data.py
index 8907d6f..646b996 100644
--- a/tests/test_data.py
+++ b/tests/test_data.py
@@ -126,7 +126,7 @@ def test_rolling_window_sequences(values, indices, window_size, step_size):
                           [2.345, 1.501, 5.903],
                           [1.501, 5.903, 9.116],
                           [5.903, 9.116, 3.068],
-                          [9.116, 3.068, 4.678],]),
+                          [9.116, 3.068, 4.678], ]),
                 np.array([0, 1, 2, 3, 4]))
 
     result = rolling_window_sequences(values, indices, window_size, step_size)