Datasets:

Nocare3
/

love2dapi_queries

+{
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+  "citation": "",
+  "config_name": "expand_columns_0",
+  "dataset_name": "parquet",
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+  "description": "",
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+  "features": {
+    "filename": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "anchor": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "repo_name": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "positive": {
+      "dtype": "null",
+      "_type": "Value"
+    },
+    "negative": {
+      "dtype": "null",
+      "_type": "Value"
+    },
+    "distilabel_metadata": {
+      "raw_output_multiply_queries": {
+        "dtype": "null",
+        "_type": "Value"
+      }
+    },
+    "model_name_query": {
+      "dtype": "string",
+      "_type": "Value"
+    },
+    "queries": {
+      "dtype": "null",
+      "_type": "Value"
+    },
+    "model_name_query_multiplied": {
+      "dtype": "string",
+      "_type": "Value"
+    }
+  },
+  "homepage": "",
+  "license": "",
+  "size_in_bytes": 177935,
+  "splits": {
+    "train": {
+      "name": "train",
+      "num_bytes": 110540,
+      "num_examples": 211,
+      "dataset_name": "parquet"
+    }
+  },
+  "version": {
+    "version_str": "0.0.0",
+    "major": 0,
+    "minor": 0,
+    "patch": 0
+  }
+}

default/train/state.json ADDED Viewed

	@@ -0,0 +1,13 @@

+{
+  "_data_files": [
+    {
+      "filename": "data-00000-of-00001.arrow"
+    }
+  ],
+  "_fingerprint": "629e334d460621ce",
+  "_format_columns": null,
+  "_format_kwargs": {},
+  "_format_type": null,
+  "_output_all_columns": false,
+  "_split": "train"
+}

distiset_configs/README.md ADDED Viewed

	@@ -0,0 +1,73 @@

+---
+size_categories: n<1K
+tags:
+- synthetic
+- distilabel
+- rlaif
+---
+<p align="left">
+  <a href="https://github.com/argilla-io/distilabel">
+    <img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/>
+  </a>
+</p>
+# Dataset Card for love2dapi_queries
+This dataset has been created with [distilabel](https://distilabel.argilla.io/).
+## Dataset Summary
+This dataset contains a `pipeline.yaml` which can be used to reproduce the pipeline that generated it in distilabel using the `distilabel` CLI:
+```console
+distilabel pipeline run --config "https://huggingface.co/datasets/love2dapi_queries/raw/main/pipeline.yaml"
+```
+or explore the configuration:
+```console
+distilabel pipeline info --config "https://huggingface.co/datasets/love2dapi_queries/raw/main/pipeline.yaml"
+```
+## Dataset structure
+The examples have the following structure per configuration:
+<details><summary> Configuration: default </summary><hr>
+```json
+{
+    "anchor": "description: Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency.\nhide: navigation\n\nWelcome to Argilla\n\nArgilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency.",
+    "distilabel_metadata": {
+        "raw_output_multiply_queries": null
+    },
+    "filename": "argilla-python/docs/index.md",
+    "model_name_query": "meta-llama/Meta-Llama-3-70B-Instruct",
+    "model_name_query_multiplied": "meta-llama/Meta-Llama-3-70B-Instruct",
+    "negative": null,
+    "positive": null,
+    "queries": null,
+    "repo_name": "argilla-io/argilla-python"
+}
+```
+This subset can be loaded as:
+```python
+from datasets import load_dataset
+ds = load_dataset("love2dapi_queries", "default")
+```
+Or simply as it follows, since there's only one configuration and is named `default`:
+```python
+from datasets import load_dataset
+ds = load_dataset("love2dapi_queries")
+```
+</details>

distiset_configs/pipeline.log ADDED Viewed

	@@ -0,0 +1,38 @@

+[2024-07-19 16:51:10] WARNING  Since the `base_url=https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-70B-Instruct` is available and either one of `model_id` or `endpoint_name` is also provided, the `base_url` will either be ignored or overwritten with the one generated from either of those args, for serverless or dedicated inference endpoints, respectively.
+[2024-07-19 16:51:10] WARNING  Since the `base_url=https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-70B-Instruct` is available and either one of `model_id` or `endpoint_name` is also provided, the `base_url` will either be ignored or overwritten with the one generated from either of those args, for serverless or dedicated inference endpoints, respectively.
+[2024-07-19 16:53:15] WARNING  Since the `base_url=https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-70B-Instruct` is available and either one of `model_id` or `endpoint_name` is also provided, the `base_url` will either be ignored or overwritten with the one generated from either of those args, for serverless or dedicated inference endpoints, respectively.
+[2024-07-19 16:53:15] WARNING  Since the `base_url=https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-70B-Instruct` is available and either one of `model_id` or `endpoint_name` is also provided, the `base_url` will either be ignored or overwritten with the one generated from either of those args, for serverless or dedicated inference endpoints, respectively.
+[2024-07-19 17:03:37] WARNING  Since the `base_url=https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-70B-Instruct` is available and either one of `model_id` or `endpoint_name` is also provided, the `base_url` will either be ignored or overwritten with the one generated from either of those args, for serverless or dedicated inference endpoints, respectively.
+[2024-07-19 17:03:37] WARNING  Since the `base_url=https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-70B-Instruct` is available and either one of `model_id` or `endpoint_name` is also provided, the `base_url` will either be ignored or overwritten with the one generated from either of those args, for serverless or dedicated inference endpoints, respectively.
+[2024-07-19 17:03:52] WARNING  Task 'multiply_queries' failed to format output: 'NoneType' object has no attribute 'split'. Saving raw response.
+[2024-07-19 17:03:52] WARNING  Subprocess traceback:
+Traceback (most recent call last):
+  File "C:\Users\Andi\Python projects\RAGTesting\.venv\Lib\site-packages\distilabel\pipeline\local.py", line 512, in _non_generator_process_loop
+    result = next(self.step.process_applying_mappings(*batch.data))
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\Andi\Python projects\RAGTesting\.venv\Lib\site-packages\distilabel\steps\base.py", line 512, in process_applying_mappings
+    for output_rows in generator:
+  File "C:\Users\Andi\Python projects\RAGTesting\.venv\Lib\site-packages\distilabel\steps\combine.py", line 119, in process
+    yield combine_dicts(
+          ^^^^^^^^^^^^^^
+  File "C:\Users\Andi\Python projects\RAGTesting\.venv\Lib\site-packages\distilabel\pipeline\utils.py", line 39, in combine_dicts
+    raise ValueError(
+ValueError: The length of output_merge_keys must be the same as the length of merge_keys
+[2024-07-19 17:03:52] WARNING  Subprocess traceback:
+Traceback (most recent call last):
+  File "C:\Users\Andi\Python projects\RAGTesting\.venv\Lib\site-packages\distilabel\pipeline\local.py", line 512, in _non_generator_process_loop
+    result = next(self.step.process_applying_mappings(*batch.data))
+             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\Andi\Python projects\RAGTesting\.venv\Lib\site-packages\distilabel\steps\base.py", line 512, in process_applying_mappings
+    for output_rows in generator:
+  File "C:\Users\Andi\Python projects\RAGTesting\.venv\Lib\site-packages\distilabel\steps\expand.py", line 111, in process
+    yield [row for input in inputs for row in self._expand_columns(input)]
+                                              ^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "C:\Users\Andi\Python projects\RAGTesting\.venv\Lib\site-packages\distilabel\steps\expand.py", line 126, in _expand_columns
+    for item, expanded in zip_longest(*[data, expanded_rows], fillvalue=input):
+                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+TypeError: 'NoneType' object is not iterable

distiset_configs/pipeline.yaml ADDED Viewed

	@@ -0,0 +1,334 @@

+distilabel:
+  version: 1.2.2
+pipeline:
+  connections:
+  - from: load_data
+    to:
+    - generate_sentence_pair
+  - from: generate_sentence_pair
+    to:
+    - multiply_queries
+  - from: multiply_queries
+    to:
+    - merge_columns
+  - from: merge_columns
+    to:
+    - expand_columns_0
+  - from: expand_columns_0
+    to: []
+  description: Generate queries to train a sentence embedding model.
+  name: embedding-queries
+  routing_batch_functions: []
+  steps:
+  - name: load_data
+    step:
+      batch_size: 10
+      config: null
+      input_mappings: {}
+      name: load_data
+      num_examples: null
+      output_mappings:
+        chunks: anchor
+      repo_id: Nocare3/love2dapi_chunks
+      runtime_parameters_info:
+      - description: The number of rows that will contain the batches generated by
+          the step.
+        name: batch_size
+        optional: true
+      - description: The Hugging Face Hub repository ID of the dataset to load.
+        name: repo_id
+        optional: false
+      - description: The split of the dataset to load. Defaults to 'train'.
+        name: split
+        optional: true
+      - description: The configuration of the dataset to load. This is optional and
+          only needed if the dataset has multiple configurations.
+        name: config
+        optional: true
+      - description: Whether to load the dataset in streaming mode or not. Defaults
+          to False.
+        name: streaming
+        optional: true
+      - description: The number of examples to load from the dataset. By default will
+          load all examples.
+        name: num_examples
+        optional: true
+      split: train
+      storage_options: null
+      streaming: false
+      type_info:
+        module: distilabel.steps.generators.huggingface
+        name: LoadDataFromHub
+  - name: generate_sentence_pair
+    step:
+      action: query
+      add_raw_output: true
+      context: The generated sentence has to be related with Love2d, a lua-code game
+        engine used mostly by indie developers.
+      group_generations: false
+      input_batch_size: 10
+      input_mappings: {}
+      llm:
+        base_url: null
+        endpoint_name: null
+        endpoint_namespace: null
+        generation_kwargs:
+          max_new_tokens: 512
+          temperature: 0.7
+        model_display_name: null
+        model_id: meta-llama/Meta-Llama-3-70B-Instruct
+        structured_output: null
+        tokenizer_id: meta-llama/Meta-Llama-3-70B-Instruct
+        type_info:
+          module: distilabel.llms.huggingface.inference_endpoints
+          name: InferenceEndpointsLLM
+        use_openai_client: false
+      name: generate_sentence_pair
+      num_generations: 1
+      output_mappings:
+        model_name: model_name_query
+      runtime_parameters_info:
+      - description: The number of rows that will contain the batches processed by
+          the step.
+        name: input_batch_size
+        optional: true
+      - name: llm
+        runtime_parameters_info:
+        - description: The kwargs to be propagated to either `generate` or `agenerate`
+            methods within each `LLM`.
+          keys:
+          - description: the maximum number of new tokens that the model will generate.  Defaults
+              to `128`.
+            name: max_new_tokens
+            optional: true
+          - description: the repetition penalty to use for the generation. Defaults  to
+              `0.0`. Only applies if `use_openai_client=True`.
+            name: frequency_penalty
+            optional: true
+          - description: the presence penalty to use for the generation. Defaults
+              to  `0.0`. Only applies if `use_openai_client=True`.
+            name: presence_penalty
+            optional: true
+          - description: the repetition penalty to use for the generation. Defaults  to
+              `None`. Only applies if `use_openai_client=False`.
+            name: repetition_penalty
+            optional: true
+          - description: the temperature to use for the generation. Defaults to `1.0`.
+            name: temperature
+            optional: true
+          - description: whether to use sampling for the generation. Defaults to `False`.  Only
+              applies if `use_openai_client=False`.
+            name: do_sample
+            optional: true
+          - description: the top-k value to use for the generation. Defaults to `0.8`,
+              since neither  `0.0` nor `1.0` are valid values in TGI.
+            name: top_k
+            optional: true
+          - description: the top-p value to use for the generation. Defaults to `1.0`.
+            name: top_p
+            optional: true
+          - description: the typical-p value to use for the generation. Defaults to
+              `0.5`.
+            name: typical_p
+            optional: true
+          - description: either a single string or a list of strings containing the
+              sequences  to stop the generation at. Defaults to `None`, but will be
+              set to the  `tokenizer.eos_token` if available.
+            name: stop_sequences
+            optional: true
+          - description: whether to return the full text of the completion or just
+              the  generated text. Defaults to `False`, meaning that only the generated
+              text will be  returned.
+            name: return_full_text
+            optional: true
+          - description: the seed to use for the generation. Defaults to `None`.
+            name: seed
+            optional: true
+          - description: whether to add the watermark to the generated text. Defaults
+              to `None`.
+            name: watermark
+            optional: true
+          name: generation_kwargs
+        - description: The name of the Inference Endpoint to use for the LLM.
+          name: endpoint_name
+          optional: true
+        - description: The namespace of the Inference Endpoint to use for the LLM.
+          name: endpoint_namespace
+          optional: true
+        - description: The base URL to use for the Inference Endpoints API requests.
+          name: base_url
+          optional: true
+        - description: The API key to authenticate the requests to the Inference Endpoints
+            API.
+          name: api_key
+          optional: true
+        - description: The structured output format to use across all the generations.
+          name: structured_output
+          optional: true
+      - description: Whether to include the raw output of the LLM in the key `raw_output_<TASK_NAME>`
+          of the `distilabel_metadata` dictionary output column
+        name: add_raw_output
+        optional: true
+      - description: The number of generations to be produced per input.
+        name: num_generations
+        optional: true
+      triplet: true
+      type_info:
+        module: distilabel.steps.tasks.sentence_transformers
+        name: GenerateSentencePair
+  - name: multiply_queries
+    step:
+      add_raw_output: true
+      group_generations: false
+      input_batch_size: 10
+      input_mappings:
+        query: positive
+      llm:
+        base_url: null
+        endpoint_name: null
+        endpoint_namespace: null
+        generation_kwargs:
+          max_new_tokens: 512
+          temperature: 0.7
+        model_display_name: null
+        model_id: meta-llama/Meta-Llama-3-70B-Instruct
+        structured_output: null
+        tokenizer_id: meta-llama/Meta-Llama-3-70B-Instruct
+        type_info:
+          module: distilabel.llms.huggingface.inference_endpoints
+          name: InferenceEndpointsLLM
+        use_openai_client: false
+      name: multiply_queries
+      num_generations: 1
+      num_queries: 3
+      output_mappings:
+        model_name: model_name_query_multiplied
+      runtime_parameters_info:
+      - description: The number of rows that will contain the batches processed by
+          the step.
+        name: input_batch_size
+        optional: true
+      - name: llm
+        runtime_parameters_info:
+        - description: The kwargs to be propagated to either `generate` or `agenerate`
+            methods within each `LLM`.
+          keys:
+          - description: the maximum number of new tokens that the model will generate.  Defaults
+              to `128`.
+            name: max_new_tokens
+            optional: true
+          - description: the repetition penalty to use for the generation. Defaults  to
+              `0.0`. Only applies if `use_openai_client=True`.
+            name: frequency_penalty
+            optional: true
+          - description: the presence penalty to use for the generation. Defaults
+              to  `0.0`. Only applies if `use_openai_client=True`.
+            name: presence_penalty
+            optional: true
+          - description: the repetition penalty to use for the generation. Defaults  to
+              `None`. Only applies if `use_openai_client=False`.
+            name: repetition_penalty
+            optional: true
+          - description: the temperature to use for the generation. Defaults to `1.0`.
+            name: temperature
+            optional: true
+          - description: whether to use sampling for the generation. Defaults to `False`.  Only
+              applies if `use_openai_client=False`.
+            name: do_sample
+            optional: true
+          - description: the top-k value to use for the generation. Defaults to `0.8`,
+              since neither  `0.0` nor `1.0` are valid values in TGI.
+            name: top_k
+            optional: true
+          - description: the top-p value to use for the generation. Defaults to `1.0`.
+            name: top_p
+            optional: true
+          - description: the typical-p value to use for the generation. Defaults to
+              `0.5`.
+            name: typical_p
+            optional: true
+          - description: either a single string or a list of strings containing the
+              sequences  to stop the generation at. Defaults to `None`, but will be
+              set to the  `tokenizer.eos_token` if available.
+            name: stop_sequences
+            optional: true
+          - description: whether to return the full text of the completion or just
+              the  generated text. Defaults to `False`, meaning that only the generated
+              text will be  returned.
+            name: return_full_text
+            optional: true
+          - description: the seed to use for the generation. Defaults to `None`.
+            name: seed
+            optional: true
+          - description: whether to add the watermark to the generated text. Defaults
+              to `None`.
+            name: watermark
+            optional: true
+          name: generation_kwargs
+        - description: The name of the Inference Endpoint to use for the LLM.
+          name: endpoint_name
+          optional: true
+        - description: The namespace of the Inference Endpoint to use for the LLM.
+          name: endpoint_namespace
+          optional: true
+        - description: The base URL to use for the Inference Endpoints API requests.
+          name: base_url
+          optional: true
+        - description: The API key to authenticate the requests to the Inference Endpoints
+            API.
+          name: api_key
+          optional: true
+        - description: The structured output format to use across all the generations.
+          name: structured_output
+          optional: true
+      - description: Whether to include the raw output of the LLM in the key `raw_output_<TASK_NAME>`
+          of the `distilabel_metadata` dictionary output column
+        name: add_raw_output
+        optional: true
+      - description: The number of generations to be produced per input.
+        name: num_generations
+        optional: true
+      system_prompt: You are an AI assistant helping to generate diverse examples.
+        Ensure the generated queries are all in separated lines and preceded by a
+        dash. Do not generate anything else or introduce the task.
+      type_info:
+        module: __main__
+        name: MultipleQueries
+  - name: merge_columns
+    step:
+      columns:
+        '0': positive
+        '1': queries
+      input_batch_size: 50
+      input_mappings: {}
+      name: merge_columns
+      output_columns:
+        '0': positive
+      output_mappings: {}
+      runtime_parameters_info:
+      - description: The number of rows that will contain the batches processed by
+          the step.
+        name: input_batch_size
+        optional: true
+      type_info:
+        module: distilabel.steps.combine
+        name: CombineColumns
+  - name: expand_columns_0
+    step:
+      columns:
+        positive: positive
+      input_batch_size: 50
+      input_mappings: {}
+      name: expand_columns_0
+      output_mappings: {}
+      runtime_parameters_info:
+      - description: The number of rows that will contain the batches processed by
+          the step.
+        name: input_batch_size
+        optional: true
+      type_info:
+        module: distilabel.steps.expand
+        name: ExpandColumns
+  type_info:
+    module: distilabel.pipeline.local
+    name: Pipeline