Text Generation
PEFT
Safetensors
English
gpt-j
lora
reasoning
thinking
sft
qwen3-template
conversational
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Add model card

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  ---
 
 
 
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  base_model: EleutherAI/gpt-j-6b
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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:EleutherAI/gpt-j-6b
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  - lora
 
 
 
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  - sft
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- - transformers
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- - trl
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- - unsloth
 
 
 
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  ---
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- # Model Card for Model ID
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-
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- <!-- Provide a quick summary of what the model is/does. -->
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-
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-
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- ## Model Details
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-
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- ### Model Description
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-
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- <!-- Provide a longer summary of what this model is. -->
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-
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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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-
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- ### Model Sources [optional]
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-
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- <!-- Provide the basic links for the model. -->
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-
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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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-
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- ## Uses
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-
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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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-
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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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-
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- ### Downstream Use [optional]
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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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- [More Information Needed]
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-
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- ### Out-of-Scope Use
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-
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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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-
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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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-
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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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-
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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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-
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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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- #### Hardware
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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 0.18.1
 
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  ---
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+ language:
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+ - en
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+ license: apache-2.0
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  base_model: EleutherAI/gpt-j-6b
 
 
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  tags:
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+ - gpt-j
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  - lora
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+ - peft
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+ - reasoning
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+ - thinking
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  - sft
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+ - qwen3-template
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+ datasets:
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+ - nohurry/Opus-4.6-Reasoning-3000x-filtered
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+ - TeichAI/claude-4.5-opus-high-reasoning-250x
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+ - Jackrong/Qwen3.5-reasoning-700x
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+ pipeline_tag: text-generation
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  ---
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+ # GPT-J 6B Thinking SFT · LoRA Adapter
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ Raw **LoRA adapter** (QLoRA, r=32, α=32) for
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+ [EleutherAI/gpt-j-6b](https://huggingface.co/EleutherAI/gpt-j-6b), trained with
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+ the Qwen3 chain-of-thought format.
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+ The **fully merged float16 model** (ready to use without PEFT) is at
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+ 👉 [ping98k/gpt-j-6b-thinking-sft](https://huggingface.co/ping98k/gpt-j-6b-thinking-sft)
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+ ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ## Adapter Details
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+ | Property | Value |
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+ |---|---|
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+ | **Base model** | EleutherAI/gpt-j-6b |
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+ | **LoRA rank** | 32 |
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+ | **LoRA alpha** | 32 |
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+ | **Target modules** | q_proj, k_proj, v_proj, out_proj, fc_in, fc_out |
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+ | **Trainable parameters** | ~50 M |
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+ | **Vocabulary additions** | `<|im_start|>`, `<|im_end|>`, `<think>`, `</think>` (50 404 total) |
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+ ---
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+ ## Usage with PEFT
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+ ```python
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+ import torch
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+ from peft import PeftModel
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+ base_model_id = "EleutherAI/gpt-j-6b"
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+ adapter_id = "ping98k/gpt-j-6b-thinking-sft-lora"
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+ tokenizer = AutoTokenizer.from_pretrained(adapter_id) # resized vocab
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+ model = AutoModelForCausalLM.from_pretrained(
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+ base_model_id,
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+ torch_dtype=torch.float16,
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+ device_map="auto",
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+ )
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+ model.resize_token_embeddings(len(tokenizer))
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+ model = PeftModel.from_pretrained(model, adapter_id)
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+ model.eval()
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+ ```
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+ > **Tip:** For most use cases, prefer the pre-merged model at
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+ > [ping98k/gpt-j-6b-thinking-sft](https://huggingface.co/ping98k/gpt-j-6b-thinking-sft) —
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+ > no PEFT dependency needed.
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+ ---
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+ ## License
 
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+ Apache 2.0 (inherits from EleutherAI/gpt-j-6b).