Instructions to use RajGana/codellama-coding-assistant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use RajGana/codellama-coding-assistant with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("codellama/CodeLlama-7b-Instruct-hf") model = PeftModel.from_pretrained(base_model, "RajGana/codellama-coding-assistant") - Transformers
How to use RajGana/codellama-coding-assistant with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="RajGana/codellama-coding-assistant") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("RajGana/codellama-coding-assistant", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use RajGana/codellama-coding-assistant with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "RajGana/codellama-coding-assistant" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "RajGana/codellama-coding-assistant", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/RajGana/codellama-coding-assistant
- SGLang
How to use RajGana/codellama-coding-assistant 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 "RajGana/codellama-coding-assistant" \ --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": "RajGana/codellama-coding-assistant", "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 "RajGana/codellama-coding-assistant" \ --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": "RajGana/codellama-coding-assistant", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use RajGana/codellama-coding-assistant with Docker Model Runner:
docker model run hf.co/RajGana/codellama-coding-assistant
Upload folder using huggingface_hub
Browse files- README.md +209 -0
- adapter_config.json +43 -0
- adapter_model.safetensors +3 -0
- chat_template.jinja +1 -0
- optimizer.pt +3 -0
- rng_state.pth +3 -0
- scheduler.pt +3 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +84 -0
- trainer_state.json +934 -0
- training_args.bin +3 -0
README.md
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| 1 |
+
---
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base_model: codellama/CodeLlama-7b-Instruct-hf
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library_name: peft
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pipeline_tag: text-generation
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tags:
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- base_model:adapter:codellama/CodeLlama-7b-Instruct-hf
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- lora
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- sft
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- transformers
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- trl
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---
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# Model Card for Model ID
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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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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [optional]:** [More Information Needed]
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## Uses
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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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### Direct Use
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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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[More Information Needed]
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### Downstream Use [optional]
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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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[More Information Needed]
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| 58 |
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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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
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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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[More Information Needed]
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## Training Details
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### Training Data
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<!-- 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. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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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).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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### Framework versions
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- PEFT 0.19.1
|
adapter_config.json
ADDED
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{
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| 2 |
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"alora_invocation_tokens": null,
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| 3 |
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"alpha_pattern": {},
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| 4 |
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"arrow_config": null,
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| 5 |
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"auto_mapping": null,
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| 6 |
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"base_model_name_or_path": "codellama/CodeLlama-7b-Instruct-hf",
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| 7 |
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"bias": "none",
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| 8 |
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"corda_config": null,
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| 9 |
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"ensure_weight_tying": false,
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| 10 |
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"eva_config": null,
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| 11 |
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"exclude_modules": null,
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| 12 |
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"fan_in_fan_out": false,
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| 13 |
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"inference_mode": true,
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| 14 |
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"init_lora_weights": true,
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| 15 |
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"layer_replication": null,
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| 16 |
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"layers_pattern": null,
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| 17 |
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"layers_to_transform": null,
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| 18 |
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"loftq_config": {},
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| 19 |
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"lora_alpha": 128,
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| 20 |
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"lora_bias": false,
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| 21 |
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"lora_dropout": 0.05,
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| 22 |
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"lora_ga_config": null,
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| 23 |
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"megatron_config": null,
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| 24 |
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"megatron_core": "megatron.core",
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| 25 |
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"modules_to_save": null,
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| 26 |
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"peft_type": "LORA",
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| 27 |
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"peft_version": "0.19.1",
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| 28 |
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"qalora_group_size": 16,
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| 29 |
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"r": 64,
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"rank_pattern": {},
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| 31 |
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"revision": null,
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| 32 |
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"target_modules": [
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"v_proj",
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| 34 |
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"q_proj"
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| 35 |
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],
|
| 36 |
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"target_parameters": null,
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| 37 |
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"task_type": "CAUSAL_LM",
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| 38 |
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"trainable_token_indices": null,
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| 39 |
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"use_bdlora": null,
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| 40 |
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"use_dora": false,
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| 41 |
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"use_qalora": false,
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| 42 |
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"use_rslora": false
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| 43 |
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}
|
adapter_model.safetensors
ADDED
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version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:aaaac375245c10bee51426f19ee662e6d385feacaf8ebdd6ad4b56b6d474816e
|
| 3 |
+
size 67126232
|
chat_template.jinja
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\n' + system_message + '\n<</SYS>>\n\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + content | trim + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' ' + content | trim + ' ' + eos_token }}{% endif %}{% endfor %}
|
optimizer.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ca91f528f599b98de119af1165c5f56a583c8595908ed58b07b62c0a90643acb
|
| 3 |
+
size 134326347
|
rng_state.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d53414066a8cc66c5f164b0d52592a475451894f47d53a0ffe41f86139ca54cc
|
| 3 |
+
size 14645
|
scheduler.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:35cf3627ef9f8df15d9c4864a49048fcd16b96fc23317a4c7fa79a020eac80c9
|
| 3 |
+
size 1465
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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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 |
+
"additional_special_tokens": [
|
| 3 |
+
"▁<PRE>",
|
| 4 |
+
"▁<MID>",
|
| 5 |
+
"▁<SUF>",
|
| 6 |
+
"▁<EOT>"
|
| 7 |
+
],
|
| 8 |
+
"bos_token": {
|
| 9 |
+
"content": "<s>",
|
| 10 |
+
"lstrip": false,
|
| 11 |
+
"normalized": false,
|
| 12 |
+
"rstrip": false,
|
| 13 |
+
"single_word": false
|
| 14 |
+
},
|
| 15 |
+
"eos_token": {
|
| 16 |
+
"content": "</s>",
|
| 17 |
+
"lstrip": false,
|
| 18 |
+
"normalized": false,
|
| 19 |
+
"rstrip": false,
|
| 20 |
+
"single_word": false
|
| 21 |
+
},
|
| 22 |
+
"pad_token": "</s>",
|
| 23 |
+
"unk_token": {
|
| 24 |
+
"content": "<unk>",
|
| 25 |
+
"lstrip": false,
|
| 26 |
+
"normalized": false,
|
| 27 |
+
"rstrip": false,
|
| 28 |
+
"single_word": false
|
| 29 |
+
}
|
| 30 |
+
}
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer.model
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:45ccb9c8b6b561889acea59191d66986d314e7cbd6a78abc6e49b139ca91c1e6
|
| 3 |
+
size 500058
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,84 @@
|
|
|
|
|
|
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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_bos_token": true,
|
| 3 |
+
"add_eos_token": false,
|
| 4 |
+
"added_tokens_decoder": {
|
| 5 |
+
"0": {
|
| 6 |
+
"content": "<unk>",
|
| 7 |
+
"lstrip": false,
|
| 8 |
+
"normalized": false,
|
| 9 |
+
"rstrip": false,
|
| 10 |
+
"single_word": false,
|
| 11 |
+
"special": true
|
| 12 |
+
},
|
| 13 |
+
"1": {
|
| 14 |
+
"content": "<s>",
|
| 15 |
+
"lstrip": false,
|
| 16 |
+
"normalized": false,
|
| 17 |
+
"rstrip": false,
|
| 18 |
+
"single_word": false,
|
| 19 |
+
"special": true
|
| 20 |
+
},
|
| 21 |
+
"2": {
|
| 22 |
+
"content": "</s>",
|
| 23 |
+
"lstrip": false,
|
| 24 |
+
"normalized": false,
|
| 25 |
+
"rstrip": false,
|
| 26 |
+
"single_word": false,
|
| 27 |
+
"special": true
|
| 28 |
+
},
|
| 29 |
+
"32007": {
|
| 30 |
+
"content": "▁<PRE>",
|
| 31 |
+
"lstrip": false,
|
| 32 |
+
"normalized": false,
|
| 33 |
+
"rstrip": false,
|
| 34 |
+
"single_word": false,
|
| 35 |
+
"special": true
|
| 36 |
+
},
|
| 37 |
+
"32008": {
|
| 38 |
+
"content": "▁<SUF>",
|
| 39 |
+
"lstrip": false,
|
| 40 |
+
"normalized": false,
|
| 41 |
+
"rstrip": false,
|
| 42 |
+
"single_word": false,
|
| 43 |
+
"special": true
|
| 44 |
+
},
|
| 45 |
+
"32009": {
|
| 46 |
+
"content": "▁<MID>",
|
| 47 |
+
"lstrip": false,
|
| 48 |
+
"normalized": false,
|
| 49 |
+
"rstrip": false,
|
| 50 |
+
"single_word": false,
|
| 51 |
+
"special": true
|
| 52 |
+
},
|
| 53 |
+
"32010": {
|
| 54 |
+
"content": "▁<EOT>",
|
| 55 |
+
"lstrip": false,
|
| 56 |
+
"normalized": false,
|
| 57 |
+
"rstrip": false,
|
| 58 |
+
"single_word": false,
|
| 59 |
+
"special": true
|
| 60 |
+
}
|
| 61 |
+
},
|
| 62 |
+
"additional_special_tokens": [
|
| 63 |
+
"▁<PRE>",
|
| 64 |
+
"▁<MID>",
|
| 65 |
+
"▁<SUF>",
|
| 66 |
+
"▁<EOT>"
|
| 67 |
+
],
|
| 68 |
+
"bos_token": "<s>",
|
| 69 |
+
"clean_up_tokenization_spaces": false,
|
| 70 |
+
"eos_token": "</s>",
|
| 71 |
+
"eot_token": "▁<EOT>",
|
| 72 |
+
"extra_special_tokens": {},
|
| 73 |
+
"fill_token": "<FILL_ME>",
|
| 74 |
+
"legacy": null,
|
| 75 |
+
"middle_token": "▁<MID>",
|
| 76 |
+
"model_max_length": 1000000000000000019884624838656,
|
| 77 |
+
"pad_token": "</s>",
|
| 78 |
+
"prefix_token": "▁<PRE>",
|
| 79 |
+
"sp_model_kwargs": {},
|
| 80 |
+
"suffix_token": "▁<SUF>",
|
| 81 |
+
"tokenizer_class": "CodeLlamaTokenizer",
|
| 82 |
+
"unk_token": "<unk>",
|
| 83 |
+
"use_default_system_prompt": false
|
| 84 |
+
}
|
trainer_state.json
ADDED
|
@@ -0,0 +1,934 @@
|
|
|
|
|
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training_args.bin
ADDED
|
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version https://git-lfs.github.com/spec/v1
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