Initial upload of ProseFlow-v1-360M-Instruct

README.md

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+---
+base_model: HuggingFaceTB/SmolLM-360M-Instruct
+language:
+  - en
+library_name: transformers
+license: apache-2.0
+datasets:
+  - LSXPrime/ProseFlow-Actions-v1
+tags:
+  - text-generation
+  - instruction
+  - proseflow
+  - unsloth
+  - smollm
+  - writing-assistant
+---
+
+# ProseFlow-v1-360M-Instruct
+
+**ProseFlow-v1-360M-Instruct** is a lightweight, experimental instruction-tuned model created for the [ProseFlow desktop application](https://github.com/LSXPrime/ProseFlow). This model is a fine-tune of HuggingFace's [**SmolLM-360M-Instruct**](https://huggingface.co/HuggingFaceTB/SmolLM-360M-Instruct) and was created to explore the capabilities of smaller language models on a diverse set of text-processing tasks.
+
+The model was fine-tuned on the [**ProseFlow-Actions-v1**](https://huggingface.co/datasets/LSXPrime/ProseFlow-Actions-v1) dataset.
+
+**Note:** This model is provided for research and experimental purposes and low-resource devices. For the best user experience in the ProseFlow application, the larger and more capable [`ProseFlow-v1-1.5B-Instruct`](https://huggingface.co/LSXPrime/ProseFlow-v1-1.5B-Instruct) model is strongly recommended.
+
+## Model Description
+
+ProseFlow is a universal AI text processor that allows users to create and execute custom AI "Actions" on text in any application. This model was an experiment to see if a ~360M parameter model could reliably perform the wide range of tasks defined in the training dataset.
+
+### Performance and Capabilities
+
+Evaluations show that while this model is extremely fast and has very low resource requirements, its capabilities are limited.
+
+#### Strengths:
+*   **Extremely Lightweight:** Can run on devices with very limited RAM and computational power.
+*   **Strict Formatting Adherence (sometimes):** In some cases where it understands the task, it can follow rigid formatting instructions (like creating a bulleted list) more strictly than its larger counterpart.
+*   **Simple Data Extraction:** It shows some capability in basic data extraction and formatting tasks, such as creating Markdown tables or extracting contact information.
+
+#### Weaknesses & Limitations:
+*   **Poor Reasoning:** The model struggles significantly with tasks that require logical reasoning, inference, or multi-step problem-solving. It often fails on word problems and logical puzzles.
+*   **Limited Creativity:** It is not effective at creative writing tasks like continuing a story or generating novel content. Its outputs are often repetitive or nonsensical.
+*   **Instructional Failures:** The model frequently violates the "no extra text" rule by adding conversational chatter. In many cases, it fails the task entirely and repeats the input verbatim.
+*   **Hallucination:** On some tasks (e.g., `To Paragraph`), the model hallucinates content completely unrelated to the input.
+*   **Unreliable for Complex Tasks:** It is not suitable for complex tasks like code refactoring, bug finding, or drafting professional business correspondence.
+
+### Intended Use
+
+This model is intended for **experimental use** and for users on **extremely resource-constrained systems** who are willing to accept a significant trade-off in performance and reliability. It may be suitable for a very limited subset of simple, repetitive text-formatting tasks.
+
+It is designed to be used within the **ProseFlow desktop application**, but it is **not the recommended model for general use**.
+
+## How to Use in ProseFlow
+
+1.  [Download and install the ProseFlow application](https://github.com/LSXPrime/ProseFlow/releases).
+2.  Navigate to the **Providers -> Local Provider** tab.
+3.  Click "Manage Models..." and download `ProseFlow-v1-360M-Instruct` from the "Available for Download" list.
+4.  Once downloaded, select it from the "My Models" list.
+5.  Set your "Primary Service Type" in ProseFlow to **Local**.
+6.  Be aware of the limitations described above when executing actions.
+
+## Training Details
+
+*   **Base Model:** [HuggingFaceTB/SmolLM-360M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM-360M-Instruct)
+*   **Dataset:** [LSXPrime/ProseFlow-Actions-v1](https://huggingface.co/datasets/LSXPrime/ProseFlow-Actions-v1)
+*   **Fine-tuning Library:** [Unsloth](https://github.com/unslothai/unsloth)
+*   **Fine-tuning Method:** Supervised fine-tuning on a dataset of structured instruction-input-output triplets.
+
+## License
+
+This model is licensed under the [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0).

added_tokens.json

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+{
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+}

chat_template.jinja

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+{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
+You are ProseFlow, a dedicated writing and text processing assistant, fine-tuned by LSXPrime.<|im_end|>
+' }}{% endif %}{{'<|im_start|>' + message['role'] + '
+' + message['content'] + '<|im_end|>' + '
+'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
+' }}{% endif %}

config.json

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+{
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+    "LlamaForCausalLM"
+  ],
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+  "hidden_act": "silu",
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+  "intermediate_size": 2560,
+  "is_llama_config": true,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "model_type": "llama",
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+  "pretraining_tp": 1,
+  "rms_norm_eps": 0.00001,
+  "rope_interleaved": false,
+  "rope_scaling": null,
+  "rope_theta": 100000,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers.js_config": {
+    "kv_cache_dtype": {
+      "fp16": "float16",
+      "q4f16": "float16"
+    }
+  },
+  "transformers_version": "4.55.4",
+  "use_cache": true,
+  "vocab_size": 49153
+}

generation_config.json

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+{
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+  "eos_token_id": 2,
+  "max_length": 8192,
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+}

model.safetensors

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runs/events.out.tfevents.1756336620.LSXPrime.38924.0

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special_tokens_map.json

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tokenizer_config.json

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+}