Initial Russian-Literature LoRA (DeepSeek-R1-Distill-Qwen-1.5B)

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+checkpoint-18/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,168 @@
+---
+base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+---
+language:
+- en
+tags:
+- lora
+- peft
+- causal-lm
+- literature
+- russian-literature
+- project-gutenberg
+- domain-adaptation
+- continued-pretraining
+library_name: transformers
+base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+license: other
+datasets:
+- sedthh/gutenberg_english
+model-index:
+- name: SamKash-Tolstoy
+  results: []
+---
+
+# SamKash-Tolstoy — DeepSeek LoRA (Russian Literature)
+
+**SamKash-Tolstoy** is a lightweight **LoRA adapter** trained on a curated slice of Project Gutenberg texts categorized as **Russian Literature** (public-domain subset).  
+It adapts **`deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B`** toward the long-form, reflective style typical of 19th-century Russian prose.
+
+> ⚠️ This repo contains **adapters only** (no base weights). Load them on top of the base model.
+
+---
+
+## TL;DR: Use It
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+from peft import PeftModel
+
+base_id = "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B"
+adpt_id = "YOUR_USERNAME/SamKash-Tolstoy"   # replace with your repo path
+
+tok = AutoTokenizer.from_pretrained(base_id, use_fast=True)
+
+# CPU (float32) or Apple M-series (MPS, float16)
+import torch
+device = "mps" if torch.backends.mps.is_available() else "cpu"
+dtype   = torch.float16 if device == "mps" else torch.float32
+
+base = AutoModelForCausalLM.from_pretrained(base_id, dtype=dtype)
+base.to(device)
+
+model = PeftModel.from_pretrained(base, adpt_id)
+model.config.use_cache = True  # inference = OK to re-enable KV cache
+
+gen = pipeline("text-generation", model=model, tokenizer=tok, device=-1)
+out = gen(
+    "Write a reflective paragraph about conscience and fate in an aristocratic household.",
+    max_new_tokens=200, do_sample=True, temperature=0.7, top_p=0.9
+)[0]["generated_text"]
+print(out)
+
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** Samiya & Kashif
+- **Funded by [optional]:** Self-funded (individual project)
+- **Shared by [optional]:** Samiya & Kashif
+- **Model type:** LoRA (PEFT) adapter for a decoder-only causal language model (Qwen-family, 1.5B params base)
+- **Language(s) (NLP):** English
+- **License:** N/A
+- **Finetuned from model [optional]:** deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Attribution & Basics
+
+- **Funded by [optional]:** Self-funded (individual project)
+- **Shared by [optional]:** Kashif Salahuddin (SamKash)
+- **Model type:** LoRA (PEFT) adapter for a decoder-only causal language model (Qwen-family base, 1.5B params)
+- **Language(s) (NLP):** English (`en`) — trained on English texts/metadata tagged as *Russian Literature* from Project Gutenberg
+- **License:** `other` for the adapters (base model license applies separately)
+- **Finetuned from model [optional]:** `deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B`
+
+---
+
+## Uses
+
+### Direct Use
+- Stylized long-form **generation** in the voice and conventions of 19th-century **Russian literature**.
+- Brainstorming themes, motifs, and character interiority.
+- Style-transfer scaffolding (draft → “make it sound like 19th-century Russian prose”).
+
+### Downstream Use [optional]
+- As a component in a creative-writing assistant or editor plugin.
+- Further **instruction tuning (SFT)** for tasks like summarization, theme extraction, or literature Q&A.
+- Educational demos of domain-adaptive pretraining (DAPT) using LoRA/PEFT.
+
+### Out-of-Scope Use
+- Factual or safety-critical tasks (medical, legal, financial advice).
+- Producing or implying authorship of genuine Tolstoy text.
+- Modern colloquial dialogue or code generation (not optimized for these).
+
+---
+
+## Bias, Risks, and Limitations
+
+- **Stylistic bias:** Strong tilt toward 19th-century Russian prose (long sentences, moral reflection).
+- **Content bias:** Public-domain texts may reflect **outdated social views**.
+- **Hallucination:** As a generative model, it can invent details; don’t use for factual claims.
+- **Language scope:** Focused on English; performance on other languages is not guaranteed.
+
+### Recommendations
+- Keep a **human in the loop** for editing and intent verification.
+- Avoid representing outputs as genuine text by historical authors.
+- For classroom settings, clearly label generated content as synthetic.
+
+---
+
+## How to Get Started with the Model
+
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+from peft import PeftModel
+
+base_id = "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B"
+adpt_id = "YOUR_USERNAME/SamKash-Tolstoy"  # or local folder
+
+device = "mps" if torch.backends.mps.is_available() else "cpu"
+dtype  = torch.float16 if device == "mps" else torch.float32
+
+tok = AutoTokenizer.from_pretrained(base_id, use_fast=True)
+base = AutoModelForCausalLM.from_pretrained(base_id, dtype=dtype)
+base.to(device)
+
+model = PeftModel.from_pretrained(base, adpt_id)
+model.config.use_cache = True  # inference
+
+gen = pipeline("text-generation", model=model, tokenizer=tok, device=-1)
+print(gen(
+    "Write a reflective paragraph about conscience and fate in an aristocratic household.",
+    max_new_tokens=200, do_sample=True, temperature=0.7, top_p=0.9
+)[0]["generated_text"])

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "down_proj",
+    "up_proj",
+    "k_proj",
+    "gate_proj",
+    "o_proj",
+    "v_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

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chat_template.jinja

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+{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% set ns = namespace(is_first=false, is_tool=false, is_output_first=true, system_prompt='') %}{%- for message in messages %}{%- if message['role'] == 'system' %}{% set ns.system_prompt = message['content'] %}{%- endif %}{%- endfor %}{{bos_token}}{{ns.system_prompt}}{%- for message in messages %}{%- if message['role'] == 'user' %}{%- set ns.is_tool = false -%}{{'<｜User｜>' + message['content']}}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is none %}{%- set ns.is_tool = false -%}{%- for tool in message['tool_calls']%}{%- if not ns.is_first %}{{'<｜Assistant｜><｜tool▁calls▁begin｜><｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\n' + '```json' + '\n' + tool['function']['arguments'] + '\n' + '```' + '<｜tool▁call▁end｜>'}}{%- set ns.is_first = true -%}{%- else %}{{'\n' + '<｜tool▁call▁begin｜>' + tool['type'] + '<｜tool▁sep｜>' + tool['function']['name'] + '\n' + '```json' + '\n' + tool['function']['arguments'] + '\n' + '```' + '<｜tool▁call▁end｜>'}}{{'<｜tool▁calls▁end｜><｜end▁of▁sentence｜>'}}{%- endif %}{%- endfor %}{%- endif %}{%- if message['role'] == 'assistant' and message['content'] is not none %}{%- if ns.is_tool %}{{'<｜tool▁outputs▁end｜>' + message['content'] + '<｜end▁of▁sentence｜>'}}{%- set ns.is_tool = false -%}{%- else %}{% set content = message['content'] %}{% if '</think>' in content %}{% set content = content.split('</think>')[-1] %}{% endif %}{{'<｜Assistant｜>' + content + '<｜end▁of▁sentence｜>'}}{%- endif %}{%- endif %}{%- if message['role'] == 'tool' %}{%- set ns.is_tool = true -%}{%- if ns.is_output_first %}{{'<｜tool▁outputs▁begin｜><｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- set ns.is_output_first = false %}{%- else %}{{'\n<｜tool▁output▁begin｜>' + message['content'] + '<｜tool▁output▁end｜>'}}{%- endif %}{%- endif %}{%- endfor -%}{% if ns.is_tool %}{{'<｜tool▁outputs▁end｜>'}}{% endif %}{% if add_generation_prompt and not ns.is_tool %}{{'<｜Assistant｜><think>\n'}}{% endif %}

checkpoint-18/README.md

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+---
+base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
+- lora
+- transformers
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.1

checkpoint-18/adapter_config.json

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