Text Generation
Transformers
Safetensors
GGUF
English
smollm2
lora
emotional
chat
companion
unsloth
q4_k_m
roleplay
small-model
conversational
Instructions to use jigs97022/tinyfeels-1.7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jigs97022/tinyfeels-1.7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="jigs97022/tinyfeels-1.7b") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jigs97022/tinyfeels-1.7b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use jigs97022/tinyfeels-1.7b with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf jigs97022/tinyfeels-1.7b:Q4_K_M # Run inference directly in the terminal: llama cli -hf jigs97022/tinyfeels-1.7b:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf jigs97022/tinyfeels-1.7b:Q4_K_M # Run inference directly in the terminal: llama cli -hf jigs97022/tinyfeels-1.7b:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf jigs97022/tinyfeels-1.7b:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf jigs97022/tinyfeels-1.7b:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf jigs97022/tinyfeels-1.7b:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf jigs97022/tinyfeels-1.7b:Q4_K_M
Use Docker
docker model run hf.co/jigs97022/tinyfeels-1.7b:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use jigs97022/tinyfeels-1.7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jigs97022/tinyfeels-1.7b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jigs97022/tinyfeels-1.7b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/jigs97022/tinyfeels-1.7b:Q4_K_M
- SGLang
How to use jigs97022/tinyfeels-1.7b with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "jigs97022/tinyfeels-1.7b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jigs97022/tinyfeels-1.7b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "jigs97022/tinyfeels-1.7b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jigs97022/tinyfeels-1.7b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use jigs97022/tinyfeels-1.7b with Ollama:
ollama run hf.co/jigs97022/tinyfeels-1.7b:Q4_K_M
- Unsloth Studio
How to use jigs97022/tinyfeels-1.7b with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for jigs97022/tinyfeels-1.7b to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for jigs97022/tinyfeels-1.7b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for jigs97022/tinyfeels-1.7b to start chatting
- Docker Model Runner
How to use jigs97022/tinyfeels-1.7b with Docker Model Runner:
docker model run hf.co/jigs97022/tinyfeels-1.7b:Q4_K_M
- Lemonade
How to use jigs97022/tinyfeels-1.7b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jigs97022/tinyfeels-1.7b:Q4_K_M
Run and chat with the model
lemonade run user.tinyfeels-1.7b-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Upload folder using huggingface_hub
Browse files- lora-adapter/README.md +59 -0
- lora-adapter/checkpoint-100/README.md +210 -0
- lora-adapter/checkpoint-100/adapter_config.json +52 -0
- lora-adapter/checkpoint-100/adapter_model.safetensors +3 -0
- lora-adapter/checkpoint-100/chat_template.jinja +6 -0
- lora-adapter/checkpoint-100/optimizer.pt +3 -0
- lora-adapter/checkpoint-100/rng_state.pth +3 -0
- lora-adapter/checkpoint-100/scaler.pt +3 -0
- lora-adapter/checkpoint-100/scheduler.pt +3 -0
- lora-adapter/checkpoint-100/tokenizer.json +0 -0
- lora-adapter/checkpoint-100/tokenizer_config.json +173 -0
- lora-adapter/checkpoint-100/trainer_state.json +112 -0
- lora-adapter/checkpoint-100/training_args.bin +3 -0
- lora-adapter/checkpoint-200/README.md +210 -0
- lora-adapter/checkpoint-200/adapter_config.json +52 -0
- lora-adapter/checkpoint-200/adapter_model.safetensors +3 -0
- lora-adapter/checkpoint-200/chat_template.jinja +6 -0
- lora-adapter/checkpoint-200/optimizer.pt +3 -0
- lora-adapter/checkpoint-200/rng_state.pth +3 -0
- lora-adapter/checkpoint-200/scaler.pt +3 -0
- lora-adapter/checkpoint-200/scheduler.pt +3 -0
- lora-adapter/checkpoint-200/tokenizer.json +0 -0
- lora-adapter/checkpoint-200/tokenizer_config.json +173 -0
- lora-adapter/checkpoint-200/trainer_state.json +190 -0
- lora-adapter/checkpoint-200/training_args.bin +3 -0
- lora-adapter/checkpoint-300/README.md +210 -0
- lora-adapter/checkpoint-300/adapter_config.json +52 -0
- lora-adapter/checkpoint-300/adapter_model.safetensors +3 -0
- lora-adapter/checkpoint-300/chat_template.jinja +6 -0
- lora-adapter/checkpoint-300/optimizer.pt +3 -0
- lora-adapter/checkpoint-300/rng_state.pth +3 -0
- lora-adapter/checkpoint-300/scaler.pt +3 -0
- lora-adapter/checkpoint-300/scheduler.pt +3 -0
- lora-adapter/checkpoint-300/tokenizer.json +0 -0
- lora-adapter/checkpoint-300/tokenizer_config.json +173 -0
- lora-adapter/checkpoint-300/trainer_state.json +268 -0
- lora-adapter/checkpoint-300/training_args.bin +3 -0
- lora-adapter/checkpoint-339/README.md +210 -0
- lora-adapter/checkpoint-339/adapter_config.json +52 -0
- lora-adapter/checkpoint-339/adapter_model.safetensors +3 -0
- lora-adapter/checkpoint-339/chat_template.jinja +6 -0
- lora-adapter/checkpoint-339/optimizer.pt +3 -0
- lora-adapter/checkpoint-339/rng_state.pth +3 -0
- lora-adapter/checkpoint-339/scaler.pt +3 -0
- lora-adapter/checkpoint-339/scheduler.pt +3 -0
- lora-adapter/checkpoint-339/tokenizer.json +0 -0
- lora-adapter/checkpoint-339/tokenizer_config.json +173 -0
- lora-adapter/checkpoint-339/trainer_state.json +297 -0
- lora-adapter/checkpoint-339/training_args.bin +3 -0
lora-adapter/README.md
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---
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base_model: unsloth/SmolLM2-1.7B-Instruct
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library_name: transformers
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model_name: smollm2-emotional-lora
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tags:
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- generated_from_trainer
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- sft
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- unsloth
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- trl
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licence: license
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---
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# Model Card for smollm2-emotional-lora
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This model is a fine-tuned version of [unsloth/SmolLM2-1.7B-Instruct](https://huggingface.co/unsloth/SmolLM2-1.7B-Instruct).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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```python
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from transformers import pipeline
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question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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generator = pipeline("text-generation", model="None", device="cuda")
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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print(output["generated_text"])
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```
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## Training procedure
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This model was trained with SFT.
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### Framework versions
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- TRL: 0.24.0
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- Transformers: 5.5.0
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- Pytorch: 2.11.0+cu128
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- Datasets: 4.3.0
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- Tokenizers: 0.22.2
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## Citations
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Cite TRL as:
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```bibtex
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@misc{vonwerra2022trl,
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title = {{TRL: Transformer Reinforcement Learning}},
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| 53 |
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author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
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| 54 |
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year = 2020,
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| 55 |
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journal = {GitHub repository},
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publisher = {GitHub},
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howpublished = {\url{https://github.com/huggingface/trl}}
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}
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```
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lora-adapter/checkpoint-100/README.md
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| 1 |
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---
|
| 2 |
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base_model: unsloth/SmolLM2-1.7B-Instruct
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| 3 |
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library_name: peft
|
| 4 |
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pipeline_tag: text-generation
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| 5 |
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tags:
|
| 6 |
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- base_model:adapter:unsloth/SmolLM2-1.7B-Instruct
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| 7 |
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- lora
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| 8 |
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- sft
|
| 9 |
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- transformers
|
| 10 |
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- trl
|
| 11 |
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- unsloth
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| 12 |
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---
|
| 13 |
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| 14 |
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# Model Card for Model ID
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| 15 |
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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| 23 |
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [More Information Needed]
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| 29 |
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- **Funded by [optional]:** [More Information Needed]
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| 30 |
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- **Shared by [optional]:** [More Information Needed]
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| 31 |
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- **Model type:** [More Information Needed]
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| 32 |
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- **Language(s) (NLP):** [More Information Needed]
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| 33 |
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- **License:** [More Information Needed]
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| 34 |
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- **Finetuned from model [optional]:** [More Information Needed]
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| 35 |
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### Model Sources [optional]
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| 37 |
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| 38 |
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<!-- Provide the basic links for the model. -->
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| 39 |
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| 40 |
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- **Repository:** [More Information Needed]
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| 41 |
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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| 43 |
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## Uses
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| 45 |
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| 46 |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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| 47 |
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### Direct Use
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| 49 |
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| 50 |
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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| 51 |
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| 52 |
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[More Information Needed]
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| 53 |
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### Downstream Use [optional]
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| 55 |
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|
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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| 58 |
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[More Information Needed]
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| 59 |
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### Out-of-Scope Use
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| 61 |
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| 62 |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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| 64 |
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[More Information Needed]
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| 65 |
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## Bias, Risks, and Limitations
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| 67 |
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|
| 68 |
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
|
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### Recommendations
|
| 73 |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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|
| 82 |
+
[More Information Needed]
|
| 83 |
+
|
| 84 |
+
## Training Details
|
| 85 |
+
|
| 86 |
+
### Training Data
|
| 87 |
+
|
| 88 |
+
<!-- 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. -->
|
| 89 |
+
|
| 90 |
+
[More Information Needed]
|
| 91 |
+
|
| 92 |
+
### Training Procedure
|
| 93 |
+
|
| 94 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 95 |
+
|
| 96 |
+
#### Preprocessing [optional]
|
| 97 |
+
|
| 98 |
+
[More Information Needed]
|
| 99 |
+
|
| 100 |
+
|
| 101 |
+
#### Training Hyperparameters
|
| 102 |
+
|
| 103 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 104 |
+
|
| 105 |
+
#### Speeds, Sizes, Times [optional]
|
| 106 |
+
|
| 107 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 108 |
+
|
| 109 |
+
[More Information Needed]
|
| 110 |
+
|
| 111 |
+
## Evaluation
|
| 112 |
+
|
| 113 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 114 |
+
|
| 115 |
+
### Testing Data, Factors & Metrics
|
| 116 |
+
|
| 117 |
+
#### Testing Data
|
| 118 |
+
|
| 119 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 120 |
+
|
| 121 |
+
[More Information Needed]
|
| 122 |
+
|
| 123 |
+
#### Factors
|
| 124 |
+
|
| 125 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 126 |
+
|
| 127 |
+
[More Information Needed]
|
| 128 |
+
|
| 129 |
+
#### Metrics
|
| 130 |
+
|
| 131 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 132 |
+
|
| 133 |
+
[More Information Needed]
|
| 134 |
+
|
| 135 |
+
### Results
|
| 136 |
+
|
| 137 |
+
[More Information Needed]
|
| 138 |
+
|
| 139 |
+
#### Summary
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
|
| 143 |
+
## Model Examination [optional]
|
| 144 |
+
|
| 145 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 146 |
+
|
| 147 |
+
[More Information Needed]
|
| 148 |
+
|
| 149 |
+
## Environmental Impact
|
| 150 |
+
|
| 151 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 152 |
+
|
| 153 |
+
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).
|
| 154 |
+
|
| 155 |
+
- **Hardware Type:** [More Information Needed]
|
| 156 |
+
- **Hours used:** [More Information Needed]
|
| 157 |
+
- **Cloud Provider:** [More Information Needed]
|
| 158 |
+
- **Compute Region:** [More Information Needed]
|
| 159 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 160 |
+
|
| 161 |
+
## Technical Specifications [optional]
|
| 162 |
+
|
| 163 |
+
### Model Architecture and Objective
|
| 164 |
+
|
| 165 |
+
[More Information Needed]
|
| 166 |
+
|
| 167 |
+
### Compute Infrastructure
|
| 168 |
+
|
| 169 |
+
[More Information Needed]
|
| 170 |
+
|
| 171 |
+
#### Hardware
|
| 172 |
+
|
| 173 |
+
[More Information Needed]
|
| 174 |
+
|
| 175 |
+
#### Software
|
| 176 |
+
|
| 177 |
+
[More Information Needed]
|
| 178 |
+
|
| 179 |
+
## Citation [optional]
|
| 180 |
+
|
| 181 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 182 |
+
|
| 183 |
+
**BibTeX:**
|
| 184 |
+
|
| 185 |
+
[More Information Needed]
|
| 186 |
+
|
| 187 |
+
**APA:**
|
| 188 |
+
|
| 189 |
+
[More Information Needed]
|
| 190 |
+
|
| 191 |
+
## Glossary [optional]
|
| 192 |
+
|
| 193 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 194 |
+
|
| 195 |
+
[More Information Needed]
|
| 196 |
+
|
| 197 |
+
## More Information [optional]
|
| 198 |
+
|
| 199 |
+
[More Information Needed]
|
| 200 |
+
|
| 201 |
+
## Model Card Authors [optional]
|
| 202 |
+
|
| 203 |
+
[More Information Needed]
|
| 204 |
+
|
| 205 |
+
## Model Card Contact
|
| 206 |
+
|
| 207 |
+
[More Information Needed]
|
| 208 |
+
### Framework versions
|
| 209 |
+
|
| 210 |
+
- PEFT 0.19.1
|
lora-adapter/checkpoint-100/adapter_config.json
ADDED
|
@@ -0,0 +1,52 @@
|
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|
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|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": {
|
| 6 |
+
"base_model_class": "LlamaForCausalLM",
|
| 7 |
+
"parent_library": "transformers.models.llama.modeling_llama",
|
| 8 |
+
"unsloth_fixed": true
|
| 9 |
+
},
|
| 10 |
+
"base_model_name_or_path": "unsloth/SmolLM2-1.7B-Instruct",
|
| 11 |
+
"bias": "none",
|
| 12 |
+
"corda_config": null,
|
| 13 |
+
"ensure_weight_tying": false,
|
| 14 |
+
"eva_config": null,
|
| 15 |
+
"exclude_modules": null,
|
| 16 |
+
"fan_in_fan_out": false,
|
| 17 |
+
"inference_mode": true,
|
| 18 |
+
"init_lora_weights": true,
|
| 19 |
+
"layer_replication": null,
|
| 20 |
+
"layers_pattern": null,
|
| 21 |
+
"layers_to_transform": null,
|
| 22 |
+
"loftq_config": {},
|
| 23 |
+
"lora_alpha": 32,
|
| 24 |
+
"lora_bias": false,
|
| 25 |
+
"lora_dropout": 0.05,
|
| 26 |
+
"lora_ga_config": null,
|
| 27 |
+
"megatron_config": null,
|
| 28 |
+
"megatron_core": "megatron.core",
|
| 29 |
+
"modules_to_save": null,
|
| 30 |
+
"peft_type": "LORA",
|
| 31 |
+
"peft_version": "0.19.1",
|
| 32 |
+
"qalora_group_size": 16,
|
| 33 |
+
"r": 16,
|
| 34 |
+
"rank_pattern": {},
|
| 35 |
+
"revision": null,
|
| 36 |
+
"target_modules": [
|
| 37 |
+
"down_proj",
|
| 38 |
+
"up_proj",
|
| 39 |
+
"k_proj",
|
| 40 |
+
"q_proj",
|
| 41 |
+
"v_proj",
|
| 42 |
+
"o_proj",
|
| 43 |
+
"gate_proj"
|
| 44 |
+
],
|
| 45 |
+
"target_parameters": null,
|
| 46 |
+
"task_type": "CAUSAL_LM",
|
| 47 |
+
"trainable_token_indices": null,
|
| 48 |
+
"use_bdlora": null,
|
| 49 |
+
"use_dora": false,
|
| 50 |
+
"use_qalora": false,
|
| 51 |
+
"use_rslora": false
|
| 52 |
+
}
|
lora-adapter/checkpoint-100/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ca49b1abf710d89f1815ead8db4315932fd62e3ac2e80db73d0ceb3895c53920
|
| 3 |
+
size 72396376
|
lora-adapter/checkpoint-100/chat_template.jinja
ADDED
|
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
|
| 2 |
+
You are a helpful AI assistant named SmolLM, trained by Hugging Face<|im_end|>
|
| 3 |
+
' }}{% endif %}{{'<|im_start|>' + message['role'] + '
|
| 4 |
+
' + message['content'] + '<|im_end|>' + '
|
| 5 |
+
'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
|
| 6 |
+
' }}{% endif %}
|
lora-adapter/checkpoint-100/optimizer.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:bbd03fd7928dad5f3434f6d3f708945574f93c5b29b731eb020c9d938f3b68d8
|
| 3 |
+
size 37138213
|
lora-adapter/checkpoint-100/rng_state.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f441831887b262e704c48a377976cd7b95a1916beb47779992cdefe50e8f5352
|
| 3 |
+
size 14645
|
lora-adapter/checkpoint-100/scaler.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c4393a84a3109995aa1202073b039b12062e3189ed89aa0b94ef0510ba843009
|
| 3 |
+
size 1383
|
lora-adapter/checkpoint-100/scheduler.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5d7abd561cc312e8726b1c642d5f7e5ab96cceefb95f5236b6b3def7f98c4f3f
|
| 3 |
+
size 1465
|
lora-adapter/checkpoint-100/tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
lora-adapter/checkpoint-100/tokenizer_config.json
ADDED
|
@@ -0,0 +1,173 @@
|
|
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|
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|
|
|
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|
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|
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|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"backend": "tokenizers",
|
| 4 |
+
"bos_token": "<|im_start|>",
|
| 5 |
+
"clean_up_tokenization_spaces": false,
|
| 6 |
+
"eos_token": "<|im_end|>",
|
| 7 |
+
"errors": "replace",
|
| 8 |
+
"extra_special_tokens": [
|
| 9 |
+
"<|im_start|>",
|
| 10 |
+
"<|im_end|>"
|
| 11 |
+
],
|
| 12 |
+
"is_local": false,
|
| 13 |
+
"model_max_length": 8192,
|
| 14 |
+
"pad_token": "<|PAD_TOKEN|>",
|
| 15 |
+
"padding_side": "right",
|
| 16 |
+
"tokenizer_class": "GPT2Tokenizer",
|
| 17 |
+
"unk_token": "�",
|
| 18 |
+
"vocab_size": 49152,
|
| 19 |
+
"added_tokens_decoder": {
|
| 20 |
+
"0": {
|
| 21 |
+
"content": "<|endoftext|>",
|
| 22 |
+
"single_word": false,
|
| 23 |
+
"lstrip": false,
|
| 24 |
+
"rstrip": false,
|
| 25 |
+
"normalized": false,
|
| 26 |
+
"special": true
|
| 27 |
+
},
|
| 28 |
+
"1": {
|
| 29 |
+
"content": "<|im_start|>",
|
| 30 |
+
"single_word": false,
|
| 31 |
+
"lstrip": false,
|
| 32 |
+
"rstrip": false,
|
| 33 |
+
"normalized": false,
|
| 34 |
+
"special": true
|
| 35 |
+
},
|
| 36 |
+
"2": {
|
| 37 |
+
"content": "<|im_end|>",
|
| 38 |
+
"single_word": false,
|
| 39 |
+
"lstrip": false,
|
| 40 |
+
"rstrip": false,
|
| 41 |
+
"normalized": false,
|
| 42 |
+
"special": true
|
| 43 |
+
},
|
| 44 |
+
"3": {
|
| 45 |
+
"content": "<repo_name>",
|
| 46 |
+
"single_word": false,
|
| 47 |
+
"lstrip": false,
|
| 48 |
+
"rstrip": false,
|
| 49 |
+
"normalized": false,
|
| 50 |
+
"special": true
|
| 51 |
+
},
|
| 52 |
+
"4": {
|
| 53 |
+
"content": "<reponame>",
|
| 54 |
+
"single_word": false,
|
| 55 |
+
"lstrip": false,
|
| 56 |
+
"rstrip": false,
|
| 57 |
+
"normalized": false,
|
| 58 |
+
"special": true
|
| 59 |
+
},
|
| 60 |
+
"5": {
|
| 61 |
+
"content": "<file_sep>",
|
| 62 |
+
"single_word": false,
|
| 63 |
+
"lstrip": false,
|
| 64 |
+
"rstrip": false,
|
| 65 |
+
"normalized": false,
|
| 66 |
+
"special": true
|
| 67 |
+
},
|
| 68 |
+
"6": {
|
| 69 |
+
"content": "<filename>",
|
| 70 |
+
"single_word": false,
|
| 71 |
+
"lstrip": false,
|
| 72 |
+
"rstrip": false,
|
| 73 |
+
"normalized": false,
|
| 74 |
+
"special": true
|
| 75 |
+
},
|
| 76 |
+
"7": {
|
| 77 |
+
"content": "<gh_stars>",
|
| 78 |
+
"single_word": false,
|
| 79 |
+
"lstrip": false,
|
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lora-adapter/checkpoint-100/trainer_state.json
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|
lora-adapter/checkpoint-100/training_args.bin
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:5bed2516133b47b8ec32a3f5147a39523682e8fb734ef7e3dafef29759653d26
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size 5713
|
lora-adapter/checkpoint-200/README.md
ADDED
|
@@ -0,0 +1,210 @@
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|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
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|
|
|
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|
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|
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|
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|
|
|
| 1 |
+
---
|
| 2 |
+
base_model: unsloth/SmolLM2-1.7B-Instruct
|
| 3 |
+
library_name: peft
|
| 4 |
+
pipeline_tag: text-generation
|
| 5 |
+
tags:
|
| 6 |
+
- base_model:adapter:unsloth/SmolLM2-1.7B-Instruct
|
| 7 |
+
- lora
|
| 8 |
+
- sft
|
| 9 |
+
- transformers
|
| 10 |
+
- trl
|
| 11 |
+
- unsloth
|
| 12 |
+
---
|
| 13 |
+
|
| 14 |
+
# Model Card for Model ID
|
| 15 |
+
|
| 16 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
## Model Details
|
| 21 |
+
|
| 22 |
+
### Model Description
|
| 23 |
+
|
| 24 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
|
| 28 |
+
- **Developed by:** [More Information Needed]
|
| 29 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 30 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 31 |
+
- **Model type:** [More Information Needed]
|
| 32 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 33 |
+
- **License:** [More Information Needed]
|
| 34 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 35 |
+
|
| 36 |
+
### Model Sources [optional]
|
| 37 |
+
|
| 38 |
+
<!-- Provide the basic links for the model. -->
|
| 39 |
+
|
| 40 |
+
- **Repository:** [More Information Needed]
|
| 41 |
+
- **Paper [optional]:** [More Information Needed]
|
| 42 |
+
- **Demo [optional]:** [More Information Needed]
|
| 43 |
+
|
| 44 |
+
## Uses
|
| 45 |
+
|
| 46 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 47 |
+
|
| 48 |
+
### Direct Use
|
| 49 |
+
|
| 50 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 51 |
+
|
| 52 |
+
[More Information Needed]
|
| 53 |
+
|
| 54 |
+
### Downstream Use [optional]
|
| 55 |
+
|
| 56 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 57 |
+
|
| 58 |
+
[More Information Needed]
|
| 59 |
+
|
| 60 |
+
### Out-of-Scope Use
|
| 61 |
+
|
| 62 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 63 |
+
|
| 64 |
+
[More Information Needed]
|
| 65 |
+
|
| 66 |
+
## Bias, Risks, and Limitations
|
| 67 |
+
|
| 68 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 69 |
+
|
| 70 |
+
[More Information Needed]
|
| 71 |
+
|
| 72 |
+
### Recommendations
|
| 73 |
+
|
| 74 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 75 |
+
|
| 76 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 77 |
+
|
| 78 |
+
## How to Get Started with the Model
|
| 79 |
+
|
| 80 |
+
Use the code below to get started with the model.
|
| 81 |
+
|
| 82 |
+
[More Information Needed]
|
| 83 |
+
|
| 84 |
+
## Training Details
|
| 85 |
+
|
| 86 |
+
### Training Data
|
| 87 |
+
|
| 88 |
+
<!-- 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. -->
|
| 89 |
+
|
| 90 |
+
[More Information Needed]
|
| 91 |
+
|
| 92 |
+
### Training Procedure
|
| 93 |
+
|
| 94 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 95 |
+
|
| 96 |
+
#### Preprocessing [optional]
|
| 97 |
+
|
| 98 |
+
[More Information Needed]
|
| 99 |
+
|
| 100 |
+
|
| 101 |
+
#### Training Hyperparameters
|
| 102 |
+
|
| 103 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 104 |
+
|
| 105 |
+
#### Speeds, Sizes, Times [optional]
|
| 106 |
+
|
| 107 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 108 |
+
|
| 109 |
+
[More Information Needed]
|
| 110 |
+
|
| 111 |
+
## Evaluation
|
| 112 |
+
|
| 113 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 114 |
+
|
| 115 |
+
### Testing Data, Factors & Metrics
|
| 116 |
+
|
| 117 |
+
#### Testing Data
|
| 118 |
+
|
| 119 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 120 |
+
|
| 121 |
+
[More Information Needed]
|
| 122 |
+
|
| 123 |
+
#### Factors
|
| 124 |
+
|
| 125 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 126 |
+
|
| 127 |
+
[More Information Needed]
|
| 128 |
+
|
| 129 |
+
#### Metrics
|
| 130 |
+
|
| 131 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 132 |
+
|
| 133 |
+
[More Information Needed]
|
| 134 |
+
|
| 135 |
+
### Results
|
| 136 |
+
|
| 137 |
+
[More Information Needed]
|
| 138 |
+
|
| 139 |
+
#### Summary
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
|
| 143 |
+
## Model Examination [optional]
|
| 144 |
+
|
| 145 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 146 |
+
|
| 147 |
+
[More Information Needed]
|
| 148 |
+
|
| 149 |
+
## Environmental Impact
|
| 150 |
+
|
| 151 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 152 |
+
|
| 153 |
+
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).
|
| 154 |
+
|
| 155 |
+
- **Hardware Type:** [More Information Needed]
|
| 156 |
+
- **Hours used:** [More Information Needed]
|
| 157 |
+
- **Cloud Provider:** [More Information Needed]
|
| 158 |
+
- **Compute Region:** [More Information Needed]
|
| 159 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 160 |
+
|
| 161 |
+
## Technical Specifications [optional]
|
| 162 |
+
|
| 163 |
+
### Model Architecture and Objective
|
| 164 |
+
|
| 165 |
+
[More Information Needed]
|
| 166 |
+
|
| 167 |
+
### Compute Infrastructure
|
| 168 |
+
|
| 169 |
+
[More Information Needed]
|
| 170 |
+
|
| 171 |
+
#### Hardware
|
| 172 |
+
|
| 173 |
+
[More Information Needed]
|
| 174 |
+
|
| 175 |
+
#### Software
|
| 176 |
+
|
| 177 |
+
[More Information Needed]
|
| 178 |
+
|
| 179 |
+
## Citation [optional]
|
| 180 |
+
|
| 181 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 182 |
+
|
| 183 |
+
**BibTeX:**
|
| 184 |
+
|
| 185 |
+
[More Information Needed]
|
| 186 |
+
|
| 187 |
+
**APA:**
|
| 188 |
+
|
| 189 |
+
[More Information Needed]
|
| 190 |
+
|
| 191 |
+
## Glossary [optional]
|
| 192 |
+
|
| 193 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 194 |
+
|
| 195 |
+
[More Information Needed]
|
| 196 |
+
|
| 197 |
+
## More Information [optional]
|
| 198 |
+
|
| 199 |
+
[More Information Needed]
|
| 200 |
+
|
| 201 |
+
## Model Card Authors [optional]
|
| 202 |
+
|
| 203 |
+
[More Information Needed]
|
| 204 |
+
|
| 205 |
+
## Model Card Contact
|
| 206 |
+
|
| 207 |
+
[More Information Needed]
|
| 208 |
+
### Framework versions
|
| 209 |
+
|
| 210 |
+
- PEFT 0.19.1
|
lora-adapter/checkpoint-200/adapter_config.json
ADDED
|
@@ -0,0 +1,52 @@
|
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|
|
|
|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": {
|
| 6 |
+
"base_model_class": "LlamaForCausalLM",
|
| 7 |
+
"parent_library": "transformers.models.llama.modeling_llama",
|
| 8 |
+
"unsloth_fixed": true
|
| 9 |
+
},
|
| 10 |
+
"base_model_name_or_path": "unsloth/SmolLM2-1.7B-Instruct",
|
| 11 |
+
"bias": "none",
|
| 12 |
+
"corda_config": null,
|
| 13 |
+
"ensure_weight_tying": false,
|
| 14 |
+
"eva_config": null,
|
| 15 |
+
"exclude_modules": null,
|
| 16 |
+
"fan_in_fan_out": false,
|
| 17 |
+
"inference_mode": true,
|
| 18 |
+
"init_lora_weights": true,
|
| 19 |
+
"layer_replication": null,
|
| 20 |
+
"layers_pattern": null,
|
| 21 |
+
"layers_to_transform": null,
|
| 22 |
+
"loftq_config": {},
|
| 23 |
+
"lora_alpha": 32,
|
| 24 |
+
"lora_bias": false,
|
| 25 |
+
"lora_dropout": 0.05,
|
| 26 |
+
"lora_ga_config": null,
|
| 27 |
+
"megatron_config": null,
|
| 28 |
+
"megatron_core": "megatron.core",
|
| 29 |
+
"modules_to_save": null,
|
| 30 |
+
"peft_type": "LORA",
|
| 31 |
+
"peft_version": "0.19.1",
|
| 32 |
+
"qalora_group_size": 16,
|
| 33 |
+
"r": 16,
|
| 34 |
+
"rank_pattern": {},
|
| 35 |
+
"revision": null,
|
| 36 |
+
"target_modules": [
|
| 37 |
+
"down_proj",
|
| 38 |
+
"up_proj",
|
| 39 |
+
"k_proj",
|
| 40 |
+
"q_proj",
|
| 41 |
+
"v_proj",
|
| 42 |
+
"o_proj",
|
| 43 |
+
"gate_proj"
|
| 44 |
+
],
|
| 45 |
+
"target_parameters": null,
|
| 46 |
+
"task_type": "CAUSAL_LM",
|
| 47 |
+
"trainable_token_indices": null,
|
| 48 |
+
"use_bdlora": null,
|
| 49 |
+
"use_dora": false,
|
| 50 |
+
"use_qalora": false,
|
| 51 |
+
"use_rslora": false
|
| 52 |
+
}
|
lora-adapter/checkpoint-200/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:712e1ec776aca02cc0fd090f39729a2f53fa7ae3b457ee3fb8ca9cf084876c7c
|
| 3 |
+
size 72396376
|
lora-adapter/checkpoint-200/chat_template.jinja
ADDED
|
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
|
| 2 |
+
You are a helpful AI assistant named SmolLM, trained by Hugging Face<|im_end|>
|
| 3 |
+
' }}{% endif %}{{'<|im_start|>' + message['role'] + '
|
| 4 |
+
' + message['content'] + '<|im_end|>' + '
|
| 5 |
+
'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
|
| 6 |
+
' }}{% endif %}
|
lora-adapter/checkpoint-200/optimizer.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ca61da4fbe99c680987b59c751b7c16873e6f394c41648845162cea242772ed5
|
| 3 |
+
size 37138213
|
lora-adapter/checkpoint-200/rng_state.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:386d6f2a299e7266f793e6f69aa7e72d835903558495ca678158c0a5b030508d
|
| 3 |
+
size 14645
|
lora-adapter/checkpoint-200/scaler.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:124625e167eb28acbfc793cfcb3e8a08b32e7fea06501462bc9e420a5e1beb2a
|
| 3 |
+
size 1383
|
lora-adapter/checkpoint-200/scheduler.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:22ce57635b2c45eb8e1f8167e5dc87b749a7080debef60762a49549291d95cb1
|
| 3 |
+
size 1465
|
lora-adapter/checkpoint-200/tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
lora-adapter/checkpoint-200/tokenizer_config.json
ADDED
|
@@ -0,0 +1,173 @@
|
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|
|
|
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|
|
|
|
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|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"backend": "tokenizers",
|
| 4 |
+
"bos_token": "<|im_start|>",
|
| 5 |
+
"clean_up_tokenization_spaces": false,
|
| 6 |
+
"eos_token": "<|im_end|>",
|
| 7 |
+
"errors": "replace",
|
| 8 |
+
"extra_special_tokens": [
|
| 9 |
+
"<|im_start|>",
|
| 10 |
+
"<|im_end|>"
|
| 11 |
+
],
|
| 12 |
+
"is_local": false,
|
| 13 |
+
"model_max_length": 8192,
|
| 14 |
+
"pad_token": "<|PAD_TOKEN|>",
|
| 15 |
+
"padding_side": "right",
|
| 16 |
+
"tokenizer_class": "GPT2Tokenizer",
|
| 17 |
+
"unk_token": "�",
|
| 18 |
+
"vocab_size": 49152,
|
| 19 |
+
"added_tokens_decoder": {
|
| 20 |
+
"0": {
|
| 21 |
+
"content": "<|endoftext|>",
|
| 22 |
+
"single_word": false,
|
| 23 |
+
"lstrip": false,
|
| 24 |
+
"rstrip": false,
|
| 25 |
+
"normalized": false,
|
| 26 |
+
"special": true
|
| 27 |
+
},
|
| 28 |
+
"1": {
|
| 29 |
+
"content": "<|im_start|>",
|
| 30 |
+
"single_word": false,
|
| 31 |
+
"lstrip": false,
|
| 32 |
+
"rstrip": false,
|
| 33 |
+
"normalized": false,
|
| 34 |
+
"special": true
|
| 35 |
+
},
|
| 36 |
+
"2": {
|
| 37 |
+
"content": "<|im_end|>",
|
| 38 |
+
"single_word": false,
|
| 39 |
+
"lstrip": false,
|
| 40 |
+
"rstrip": false,
|
| 41 |
+
"normalized": false,
|
| 42 |
+
"special": true
|
| 43 |
+
},
|
| 44 |
+
"3": {
|
| 45 |
+
"content": "<repo_name>",
|
| 46 |
+
"single_word": false,
|
| 47 |
+
"lstrip": false,
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| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5bed2516133b47b8ec32a3f5147a39523682e8fb734ef7e3dafef29759653d26
|
| 3 |
+
size 5713
|
lora-adapter/checkpoint-300/README.md
ADDED
|
@@ -0,0 +1,210 @@
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| 1 |
+
---
|
| 2 |
+
base_model: unsloth/SmolLM2-1.7B-Instruct
|
| 3 |
+
library_name: peft
|
| 4 |
+
pipeline_tag: text-generation
|
| 5 |
+
tags:
|
| 6 |
+
- base_model:adapter:unsloth/SmolLM2-1.7B-Instruct
|
| 7 |
+
- lora
|
| 8 |
+
- sft
|
| 9 |
+
- transformers
|
| 10 |
+
- trl
|
| 11 |
+
- unsloth
|
| 12 |
+
---
|
| 13 |
+
|
| 14 |
+
# Model Card for Model ID
|
| 15 |
+
|
| 16 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
## Model Details
|
| 21 |
+
|
| 22 |
+
### Model Description
|
| 23 |
+
|
| 24 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
|
| 28 |
+
- **Developed by:** [More Information Needed]
|
| 29 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 30 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 31 |
+
- **Model type:** [More Information Needed]
|
| 32 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 33 |
+
- **License:** [More Information Needed]
|
| 34 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 35 |
+
|
| 36 |
+
### Model Sources [optional]
|
| 37 |
+
|
| 38 |
+
<!-- Provide the basic links for the model. -->
|
| 39 |
+
|
| 40 |
+
- **Repository:** [More Information Needed]
|
| 41 |
+
- **Paper [optional]:** [More Information Needed]
|
| 42 |
+
- **Demo [optional]:** [More Information Needed]
|
| 43 |
+
|
| 44 |
+
## Uses
|
| 45 |
+
|
| 46 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 47 |
+
|
| 48 |
+
### Direct Use
|
| 49 |
+
|
| 50 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 51 |
+
|
| 52 |
+
[More Information Needed]
|
| 53 |
+
|
| 54 |
+
### Downstream Use [optional]
|
| 55 |
+
|
| 56 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 57 |
+
|
| 58 |
+
[More Information Needed]
|
| 59 |
+
|
| 60 |
+
### Out-of-Scope Use
|
| 61 |
+
|
| 62 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 63 |
+
|
| 64 |
+
[More Information Needed]
|
| 65 |
+
|
| 66 |
+
## Bias, Risks, and Limitations
|
| 67 |
+
|
| 68 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 69 |
+
|
| 70 |
+
[More Information Needed]
|
| 71 |
+
|
| 72 |
+
### Recommendations
|
| 73 |
+
|
| 74 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 75 |
+
|
| 76 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 77 |
+
|
| 78 |
+
## How to Get Started with the Model
|
| 79 |
+
|
| 80 |
+
Use the code below to get started with the model.
|
| 81 |
+
|
| 82 |
+
[More Information Needed]
|
| 83 |
+
|
| 84 |
+
## Training Details
|
| 85 |
+
|
| 86 |
+
### Training Data
|
| 87 |
+
|
| 88 |
+
<!-- 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. -->
|
| 89 |
+
|
| 90 |
+
[More Information Needed]
|
| 91 |
+
|
| 92 |
+
### Training Procedure
|
| 93 |
+
|
| 94 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 95 |
+
|
| 96 |
+
#### Preprocessing [optional]
|
| 97 |
+
|
| 98 |
+
[More Information Needed]
|
| 99 |
+
|
| 100 |
+
|
| 101 |
+
#### Training Hyperparameters
|
| 102 |
+
|
| 103 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 104 |
+
|
| 105 |
+
#### Speeds, Sizes, Times [optional]
|
| 106 |
+
|
| 107 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 108 |
+
|
| 109 |
+
[More Information Needed]
|
| 110 |
+
|
| 111 |
+
## Evaluation
|
| 112 |
+
|
| 113 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 114 |
+
|
| 115 |
+
### Testing Data, Factors & Metrics
|
| 116 |
+
|
| 117 |
+
#### Testing Data
|
| 118 |
+
|
| 119 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 120 |
+
|
| 121 |
+
[More Information Needed]
|
| 122 |
+
|
| 123 |
+
#### Factors
|
| 124 |
+
|
| 125 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 126 |
+
|
| 127 |
+
[More Information Needed]
|
| 128 |
+
|
| 129 |
+
#### Metrics
|
| 130 |
+
|
| 131 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 132 |
+
|
| 133 |
+
[More Information Needed]
|
| 134 |
+
|
| 135 |
+
### Results
|
| 136 |
+
|
| 137 |
+
[More Information Needed]
|
| 138 |
+
|
| 139 |
+
#### Summary
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
|
| 143 |
+
## Model Examination [optional]
|
| 144 |
+
|
| 145 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 146 |
+
|
| 147 |
+
[More Information Needed]
|
| 148 |
+
|
| 149 |
+
## Environmental Impact
|
| 150 |
+
|
| 151 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 152 |
+
|
| 153 |
+
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).
|
| 154 |
+
|
| 155 |
+
- **Hardware Type:** [More Information Needed]
|
| 156 |
+
- **Hours used:** [More Information Needed]
|
| 157 |
+
- **Cloud Provider:** [More Information Needed]
|
| 158 |
+
- **Compute Region:** [More Information Needed]
|
| 159 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 160 |
+
|
| 161 |
+
## Technical Specifications [optional]
|
| 162 |
+
|
| 163 |
+
### Model Architecture and Objective
|
| 164 |
+
|
| 165 |
+
[More Information Needed]
|
| 166 |
+
|
| 167 |
+
### Compute Infrastructure
|
| 168 |
+
|
| 169 |
+
[More Information Needed]
|
| 170 |
+
|
| 171 |
+
#### Hardware
|
| 172 |
+
|
| 173 |
+
[More Information Needed]
|
| 174 |
+
|
| 175 |
+
#### Software
|
| 176 |
+
|
| 177 |
+
[More Information Needed]
|
| 178 |
+
|
| 179 |
+
## Citation [optional]
|
| 180 |
+
|
| 181 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 182 |
+
|
| 183 |
+
**BibTeX:**
|
| 184 |
+
|
| 185 |
+
[More Information Needed]
|
| 186 |
+
|
| 187 |
+
**APA:**
|
| 188 |
+
|
| 189 |
+
[More Information Needed]
|
| 190 |
+
|
| 191 |
+
## Glossary [optional]
|
| 192 |
+
|
| 193 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 194 |
+
|
| 195 |
+
[More Information Needed]
|
| 196 |
+
|
| 197 |
+
## More Information [optional]
|
| 198 |
+
|
| 199 |
+
[More Information Needed]
|
| 200 |
+
|
| 201 |
+
## Model Card Authors [optional]
|
| 202 |
+
|
| 203 |
+
[More Information Needed]
|
| 204 |
+
|
| 205 |
+
## Model Card Contact
|
| 206 |
+
|
| 207 |
+
[More Information Needed]
|
| 208 |
+
### Framework versions
|
| 209 |
+
|
| 210 |
+
- PEFT 0.19.1
|
lora-adapter/checkpoint-300/adapter_config.json
ADDED
|
@@ -0,0 +1,52 @@
|
|
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|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": {
|
| 6 |
+
"base_model_class": "LlamaForCausalLM",
|
| 7 |
+
"parent_library": "transformers.models.llama.modeling_llama",
|
| 8 |
+
"unsloth_fixed": true
|
| 9 |
+
},
|
| 10 |
+
"base_model_name_or_path": "unsloth/SmolLM2-1.7B-Instruct",
|
| 11 |
+
"bias": "none",
|
| 12 |
+
"corda_config": null,
|
| 13 |
+
"ensure_weight_tying": false,
|
| 14 |
+
"eva_config": null,
|
| 15 |
+
"exclude_modules": null,
|
| 16 |
+
"fan_in_fan_out": false,
|
| 17 |
+
"inference_mode": true,
|
| 18 |
+
"init_lora_weights": true,
|
| 19 |
+
"layer_replication": null,
|
| 20 |
+
"layers_pattern": null,
|
| 21 |
+
"layers_to_transform": null,
|
| 22 |
+
"loftq_config": {},
|
| 23 |
+
"lora_alpha": 32,
|
| 24 |
+
"lora_bias": false,
|
| 25 |
+
"lora_dropout": 0.05,
|
| 26 |
+
"lora_ga_config": null,
|
| 27 |
+
"megatron_config": null,
|
| 28 |
+
"megatron_core": "megatron.core",
|
| 29 |
+
"modules_to_save": null,
|
| 30 |
+
"peft_type": "LORA",
|
| 31 |
+
"peft_version": "0.19.1",
|
| 32 |
+
"qalora_group_size": 16,
|
| 33 |
+
"r": 16,
|
| 34 |
+
"rank_pattern": {},
|
| 35 |
+
"revision": null,
|
| 36 |
+
"target_modules": [
|
| 37 |
+
"down_proj",
|
| 38 |
+
"up_proj",
|
| 39 |
+
"k_proj",
|
| 40 |
+
"q_proj",
|
| 41 |
+
"v_proj",
|
| 42 |
+
"o_proj",
|
| 43 |
+
"gate_proj"
|
| 44 |
+
],
|
| 45 |
+
"target_parameters": null,
|
| 46 |
+
"task_type": "CAUSAL_LM",
|
| 47 |
+
"trainable_token_indices": null,
|
| 48 |
+
"use_bdlora": null,
|
| 49 |
+
"use_dora": false,
|
| 50 |
+
"use_qalora": false,
|
| 51 |
+
"use_rslora": false
|
| 52 |
+
}
|
lora-adapter/checkpoint-300/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9a02f0c0fb106cec5dbc7c2b2a2af2bd519a9b3f1022361d77cd942a32d5557d
|
| 3 |
+
size 72396376
|
lora-adapter/checkpoint-300/chat_template.jinja
ADDED
|
@@ -0,0 +1,6 @@
|
|
|
|
|
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|
|
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|
|
|
| 1 |
+
{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
|
| 2 |
+
You are a helpful AI assistant named SmolLM, trained by Hugging Face<|im_end|>
|
| 3 |
+
' }}{% endif %}{{'<|im_start|>' + message['role'] + '
|
| 4 |
+
' + message['content'] + '<|im_end|>' + '
|
| 5 |
+
'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
|
| 6 |
+
' }}{% endif %}
|
lora-adapter/checkpoint-300/optimizer.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
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|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ab4ebb1da3e2781a6efe0818b699571a48ac9c055f433b18e2ec120959d2e8b8
|
| 3 |
+
size 37138533
|
lora-adapter/checkpoint-300/rng_state.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
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|
|
|
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|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
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lora-adapter/checkpoint-300/tokenizer_config.json
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lora-adapter/checkpoint-300/trainer_state.json
ADDED
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size 5713
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lora-adapter/checkpoint-339/README.md
ADDED
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@@ -0,0 +1,210 @@
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|
| 1 |
+
---
|
| 2 |
+
base_model: unsloth/SmolLM2-1.7B-Instruct
|
| 3 |
+
library_name: peft
|
| 4 |
+
pipeline_tag: text-generation
|
| 5 |
+
tags:
|
| 6 |
+
- base_model:adapter:unsloth/SmolLM2-1.7B-Instruct
|
| 7 |
+
- lora
|
| 8 |
+
- sft
|
| 9 |
+
- transformers
|
| 10 |
+
- trl
|
| 11 |
+
- unsloth
|
| 12 |
+
---
|
| 13 |
+
|
| 14 |
+
# Model Card for Model ID
|
| 15 |
+
|
| 16 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
| 17 |
+
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
## Model Details
|
| 21 |
+
|
| 22 |
+
### Model Description
|
| 23 |
+
|
| 24 |
+
<!-- Provide a longer summary of what this model is. -->
|
| 25 |
+
|
| 26 |
+
|
| 27 |
+
|
| 28 |
+
- **Developed by:** [More Information Needed]
|
| 29 |
+
- **Funded by [optional]:** [More Information Needed]
|
| 30 |
+
- **Shared by [optional]:** [More Information Needed]
|
| 31 |
+
- **Model type:** [More Information Needed]
|
| 32 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 33 |
+
- **License:** [More Information Needed]
|
| 34 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
| 35 |
+
|
| 36 |
+
### Model Sources [optional]
|
| 37 |
+
|
| 38 |
+
<!-- Provide the basic links for the model. -->
|
| 39 |
+
|
| 40 |
+
- **Repository:** [More Information Needed]
|
| 41 |
+
- **Paper [optional]:** [More Information Needed]
|
| 42 |
+
- **Demo [optional]:** [More Information Needed]
|
| 43 |
+
|
| 44 |
+
## Uses
|
| 45 |
+
|
| 46 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 47 |
+
|
| 48 |
+
### Direct Use
|
| 49 |
+
|
| 50 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 51 |
+
|
| 52 |
+
[More Information Needed]
|
| 53 |
+
|
| 54 |
+
### Downstream Use [optional]
|
| 55 |
+
|
| 56 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 57 |
+
|
| 58 |
+
[More Information Needed]
|
| 59 |
+
|
| 60 |
+
### Out-of-Scope Use
|
| 61 |
+
|
| 62 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
| 63 |
+
|
| 64 |
+
[More Information Needed]
|
| 65 |
+
|
| 66 |
+
## Bias, Risks, and Limitations
|
| 67 |
+
|
| 68 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
| 69 |
+
|
| 70 |
+
[More Information Needed]
|
| 71 |
+
|
| 72 |
+
### Recommendations
|
| 73 |
+
|
| 74 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 75 |
+
|
| 76 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
| 77 |
+
|
| 78 |
+
## How to Get Started with the Model
|
| 79 |
+
|
| 80 |
+
Use the code below to get started with the model.
|
| 81 |
+
|
| 82 |
+
[More Information Needed]
|
| 83 |
+
|
| 84 |
+
## Training Details
|
| 85 |
+
|
| 86 |
+
### Training Data
|
| 87 |
+
|
| 88 |
+
<!-- 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. -->
|
| 89 |
+
|
| 90 |
+
[More Information Needed]
|
| 91 |
+
|
| 92 |
+
### Training Procedure
|
| 93 |
+
|
| 94 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
| 95 |
+
|
| 96 |
+
#### Preprocessing [optional]
|
| 97 |
+
|
| 98 |
+
[More Information Needed]
|
| 99 |
+
|
| 100 |
+
|
| 101 |
+
#### Training Hyperparameters
|
| 102 |
+
|
| 103 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
| 104 |
+
|
| 105 |
+
#### Speeds, Sizes, Times [optional]
|
| 106 |
+
|
| 107 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 108 |
+
|
| 109 |
+
[More Information Needed]
|
| 110 |
+
|
| 111 |
+
## Evaluation
|
| 112 |
+
|
| 113 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 114 |
+
|
| 115 |
+
### Testing Data, Factors & Metrics
|
| 116 |
+
|
| 117 |
+
#### Testing Data
|
| 118 |
+
|
| 119 |
+
<!-- This should link to a Dataset Card if possible. -->
|
| 120 |
+
|
| 121 |
+
[More Information Needed]
|
| 122 |
+
|
| 123 |
+
#### Factors
|
| 124 |
+
|
| 125 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 126 |
+
|
| 127 |
+
[More Information Needed]
|
| 128 |
+
|
| 129 |
+
#### Metrics
|
| 130 |
+
|
| 131 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 132 |
+
|
| 133 |
+
[More Information Needed]
|
| 134 |
+
|
| 135 |
+
### Results
|
| 136 |
+
|
| 137 |
+
[More Information Needed]
|
| 138 |
+
|
| 139 |
+
#### Summary
|
| 140 |
+
|
| 141 |
+
|
| 142 |
+
|
| 143 |
+
## Model Examination [optional]
|
| 144 |
+
|
| 145 |
+
<!-- Relevant interpretability work for the model goes here -->
|
| 146 |
+
|
| 147 |
+
[More Information Needed]
|
| 148 |
+
|
| 149 |
+
## Environmental Impact
|
| 150 |
+
|
| 151 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 152 |
+
|
| 153 |
+
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).
|
| 154 |
+
|
| 155 |
+
- **Hardware Type:** [More Information Needed]
|
| 156 |
+
- **Hours used:** [More Information Needed]
|
| 157 |
+
- **Cloud Provider:** [More Information Needed]
|
| 158 |
+
- **Compute Region:** [More Information Needed]
|
| 159 |
+
- **Carbon Emitted:** [More Information Needed]
|
| 160 |
+
|
| 161 |
+
## Technical Specifications [optional]
|
| 162 |
+
|
| 163 |
+
### Model Architecture and Objective
|
| 164 |
+
|
| 165 |
+
[More Information Needed]
|
| 166 |
+
|
| 167 |
+
### Compute Infrastructure
|
| 168 |
+
|
| 169 |
+
[More Information Needed]
|
| 170 |
+
|
| 171 |
+
#### Hardware
|
| 172 |
+
|
| 173 |
+
[More Information Needed]
|
| 174 |
+
|
| 175 |
+
#### Software
|
| 176 |
+
|
| 177 |
+
[More Information Needed]
|
| 178 |
+
|
| 179 |
+
## Citation [optional]
|
| 180 |
+
|
| 181 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 182 |
+
|
| 183 |
+
**BibTeX:**
|
| 184 |
+
|
| 185 |
+
[More Information Needed]
|
| 186 |
+
|
| 187 |
+
**APA:**
|
| 188 |
+
|
| 189 |
+
[More Information Needed]
|
| 190 |
+
|
| 191 |
+
## Glossary [optional]
|
| 192 |
+
|
| 193 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 194 |
+
|
| 195 |
+
[More Information Needed]
|
| 196 |
+
|
| 197 |
+
## More Information [optional]
|
| 198 |
+
|
| 199 |
+
[More Information Needed]
|
| 200 |
+
|
| 201 |
+
## Model Card Authors [optional]
|
| 202 |
+
|
| 203 |
+
[More Information Needed]
|
| 204 |
+
|
| 205 |
+
## Model Card Contact
|
| 206 |
+
|
| 207 |
+
[More Information Needed]
|
| 208 |
+
### Framework versions
|
| 209 |
+
|
| 210 |
+
- PEFT 0.19.1
|
lora-adapter/checkpoint-339/adapter_config.json
ADDED
|
@@ -0,0 +1,52 @@
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|
| 1 |
+
{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
+
"alpha_pattern": {},
|
| 4 |
+
"arrow_config": null,
|
| 5 |
+
"auto_mapping": {
|
| 6 |
+
"base_model_class": "LlamaForCausalLM",
|
| 7 |
+
"parent_library": "transformers.models.llama.modeling_llama",
|
| 8 |
+
"unsloth_fixed": true
|
| 9 |
+
},
|
| 10 |
+
"base_model_name_or_path": "unsloth/SmolLM2-1.7B-Instruct",
|
| 11 |
+
"bias": "none",
|
| 12 |
+
"corda_config": null,
|
| 13 |
+
"ensure_weight_tying": false,
|
| 14 |
+
"eva_config": null,
|
| 15 |
+
"exclude_modules": null,
|
| 16 |
+
"fan_in_fan_out": false,
|
| 17 |
+
"inference_mode": true,
|
| 18 |
+
"init_lora_weights": true,
|
| 19 |
+
"layer_replication": null,
|
| 20 |
+
"layers_pattern": null,
|
| 21 |
+
"layers_to_transform": null,
|
| 22 |
+
"loftq_config": {},
|
| 23 |
+
"lora_alpha": 32,
|
| 24 |
+
"lora_bias": false,
|
| 25 |
+
"lora_dropout": 0.05,
|
| 26 |
+
"lora_ga_config": null,
|
| 27 |
+
"megatron_config": null,
|
| 28 |
+
"megatron_core": "megatron.core",
|
| 29 |
+
"modules_to_save": null,
|
| 30 |
+
"peft_type": "LORA",
|
| 31 |
+
"peft_version": "0.19.1",
|
| 32 |
+
"qalora_group_size": 16,
|
| 33 |
+
"r": 16,
|
| 34 |
+
"rank_pattern": {},
|
| 35 |
+
"revision": null,
|
| 36 |
+
"target_modules": [
|
| 37 |
+
"down_proj",
|
| 38 |
+
"up_proj",
|
| 39 |
+
"k_proj",
|
| 40 |
+
"q_proj",
|
| 41 |
+
"v_proj",
|
| 42 |
+
"o_proj",
|
| 43 |
+
"gate_proj"
|
| 44 |
+
],
|
| 45 |
+
"target_parameters": null,
|
| 46 |
+
"task_type": "CAUSAL_LM",
|
| 47 |
+
"trainable_token_indices": null,
|
| 48 |
+
"use_bdlora": null,
|
| 49 |
+
"use_dora": false,
|
| 50 |
+
"use_qalora": false,
|
| 51 |
+
"use_rslora": false
|
| 52 |
+
}
|
lora-adapter/checkpoint-339/adapter_model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e9f5d4a49e19b560a51601ae02e2255f8359cbed8f8f7050a44511d7a0175c61
|
| 3 |
+
size 72396376
|
lora-adapter/checkpoint-339/chat_template.jinja
ADDED
|
@@ -0,0 +1,6 @@
|
|
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|
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|
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|
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|
|
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|
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|
|
| 1 |
+
{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
|
| 2 |
+
You are a helpful AI assistant named SmolLM, trained by Hugging Face<|im_end|>
|
| 3 |
+
' }}{% endif %}{{'<|im_start|>' + message['role'] + '
|
| 4 |
+
' + message['content'] + '<|im_end|>' + '
|
| 5 |
+
'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
|
| 6 |
+
' }}{% endif %}
|
lora-adapter/checkpoint-339/optimizer.pt
ADDED
|
@@ -0,0 +1,3 @@
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|
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|
|
|
|
|
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|
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:6c41590b3d34e2e3f8c3e299dbed1fc03340305228683d500d62daa0a20057a2
|
| 3 |
+
size 37138533
|
lora-adapter/checkpoint-339/rng_state.pth
ADDED
|
@@ -0,0 +1,3 @@
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|
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|
|
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:0b6a9c6bc12cb0ec2371d47919188be56c4525321c91056c0c8219b96596f802
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| 3 |
+
size 14645
|
lora-adapter/checkpoint-339/scaler.pt
ADDED
|
@@ -0,0 +1,3 @@
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|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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oid sha256:14bd5c75fdea9f94ec829329c0f666fd63edbc684f38f55543ab208602a15702
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| 3 |
+
size 1383
|
lora-adapter/checkpoint-339/scheduler.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
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|
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|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
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oid sha256:c3ceeb962b61bec3eb227b3256130b942e361cce57b3a45380d791246e4f6b73
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| 3 |
+
size 1465
|
lora-adapter/checkpoint-339/tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
lora-adapter/checkpoint-339/tokenizer_config.json
ADDED
|
@@ -0,0 +1,173 @@
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|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"backend": "tokenizers",
|
| 4 |
+
"bos_token": "<|im_start|>",
|
| 5 |
+
"clean_up_tokenization_spaces": false,
|
| 6 |
+
"eos_token": "<|im_end|>",
|
| 7 |
+
"errors": "replace",
|
| 8 |
+
"extra_special_tokens": [
|
| 9 |
+
"<|im_start|>",
|
| 10 |
+
"<|im_end|>"
|
| 11 |
+
],
|
| 12 |
+
"is_local": false,
|
| 13 |
+
"model_max_length": 8192,
|
| 14 |
+
"pad_token": "<|PAD_TOKEN|>",
|
| 15 |
+
"padding_side": "right",
|
| 16 |
+
"tokenizer_class": "GPT2Tokenizer",
|
| 17 |
+
"unk_token": "�",
|
| 18 |
+
"vocab_size": 49152,
|
| 19 |
+
"added_tokens_decoder": {
|
| 20 |
+
"0": {
|
| 21 |
+
"content": "<|endoftext|>",
|
| 22 |
+
"single_word": false,
|
| 23 |
+
"lstrip": false,
|
| 24 |
+
"rstrip": false,
|
| 25 |
+
"normalized": false,
|
| 26 |
+
"special": true
|
| 27 |
+
},
|
| 28 |
+
"1": {
|
| 29 |
+
"content": "<|im_start|>",
|
| 30 |
+
"single_word": false,
|
| 31 |
+
"lstrip": false,
|
| 32 |
+
"rstrip": false,
|
| 33 |
+
"normalized": false,
|
| 34 |
+
"special": true
|
| 35 |
+
},
|
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