Quantization made by Richard Erkhov. [Github](https://github.com/RichardErkhov) [Discord](https://discord.gg/pvy7H8DZMG) [Request more models](https://github.com/RichardErkhov/quant_request) Mistral-7B-v0.2-meditron-turkish - GGUF - Model creator: https://huggingface.co/malhajar/ - Original model: https://huggingface.co/malhajar/Mistral-7B-v0.2-meditron-turkish/ | Name | Quant method | Size | | ---- | ---- | ---- | | [Mistral-7B-v0.2-meditron-turkish.Q2_K.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.Q2_K.gguf) | Q2_K | 2.53GB | | [Mistral-7B-v0.2-meditron-turkish.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.IQ3_XS.gguf) | IQ3_XS | 2.81GB | | [Mistral-7B-v0.2-meditron-turkish.IQ3_S.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.IQ3_S.gguf) | IQ3_S | 2.96GB | | [Mistral-7B-v0.2-meditron-turkish.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.Q3_K_S.gguf) | Q3_K_S | 2.95GB | | [Mistral-7B-v0.2-meditron-turkish.IQ3_M.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.IQ3_M.gguf) | IQ3_M | 3.06GB | | [Mistral-7B-v0.2-meditron-turkish.Q3_K.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.Q3_K.gguf) | Q3_K | 3.28GB | | [Mistral-7B-v0.2-meditron-turkish.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.Q3_K_M.gguf) | Q3_K_M | 3.28GB | | [Mistral-7B-v0.2-meditron-turkish.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.Q3_K_L.gguf) | Q3_K_L | 3.56GB | | [Mistral-7B-v0.2-meditron-turkish.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.IQ4_XS.gguf) | IQ4_XS | 3.67GB | | [Mistral-7B-v0.2-meditron-turkish.Q4_0.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.Q4_0.gguf) | Q4_0 | 3.83GB | | [Mistral-7B-v0.2-meditron-turkish.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.IQ4_NL.gguf) | IQ4_NL | 3.87GB | | [Mistral-7B-v0.2-meditron-turkish.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.Q4_K_S.gguf) | Q4_K_S | 3.86GB | | [Mistral-7B-v0.2-meditron-turkish.Q4_K.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.Q4_K.gguf) | Q4_K | 4.07GB | | [Mistral-7B-v0.2-meditron-turkish.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.Q4_K_M.gguf) | Q4_K_M | 4.07GB | | [Mistral-7B-v0.2-meditron-turkish.Q4_1.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.Q4_1.gguf) | Q4_1 | 4.24GB | | [Mistral-7B-v0.2-meditron-turkish.Q5_0.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.Q5_0.gguf) | Q5_0 | 4.65GB | | [Mistral-7B-v0.2-meditron-turkish.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.Q5_K_S.gguf) | Q5_K_S | 4.65GB | | [Mistral-7B-v0.2-meditron-turkish.Q5_K.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.Q5_K.gguf) | Q5_K | 4.78GB | | [Mistral-7B-v0.2-meditron-turkish.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.Q5_K_M.gguf) | Q5_K_M | 4.78GB | | [Mistral-7B-v0.2-meditron-turkish.Q5_1.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.Q5_1.gguf) | Q5_1 | 5.07GB | | [Mistral-7B-v0.2-meditron-turkish.Q6_K.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.Q6_K.gguf) | Q6_K | 5.53GB | | [Mistral-7B-v0.2-meditron-turkish.Q8_0.gguf](https://huggingface.co/RichardErkhov/malhajar_-_Mistral-7B-v0.2-meditron-turkish-gguf/blob/main/Mistral-7B-v0.2-meditron-turkish.Q8_0.gguf) | Q8_0 | 7.17GB | Original model description: --- language: - tr - en license: apache-2.0 datasets: - malhajar/meditron-tr model-index: - name: Mistral-7B-v0.2-meditron-turkish results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 59.56 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 81.79 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 60.35 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 66.19 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 76.24 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 35.94 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=malhajar/Mistral-7B-v0.2-meditron-turkish name: Open LLM Leaderboard --- # Model Card for Model ID Mistral-7B-v0.2-meditron-turkish is a finetuned Mistral Model version using Freeze technique on Turkish Meditron dataset of [`malhajar/meditron-7b-tr`](https://huggingface.co/datasets/malhajar/meditron-tr) using SFT Training. This model can answer information about different excplicit ideas in medicine in Turkish and English ### Model Description - **Finetuned by:** [`Mohamad Alhajar`](https://www.linkedin.com/in/muhammet-alhajar/) - **Language(s) (NLP):** Turkish,English - **Finetuned from model:** [`mistralai/Mistral-7B-Instruct-v0.2`](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) ### Prompt Template For Turkish Generation ``` ### Kullancı: ``` ### Prompt Template For English Generation ``` ### User: ``` ## How to Get Started with the Model Use the code sample provided in the original post to interact with the model. ```python from transformers import AutoTokenizer,AutoModelForCausalLM model_id = "malhajar/Mistral-7B-v0.2-meditron-turkish" model = AutoModelForCausalLM.from_pretrained(model_name_or_path, device_map="auto", torch_dtype=torch.float16, revision="main") tokenizer = AutoTokenizer.from_pretrained(model_id) question: "Akciğer kanseri nedir?" # For generating a response prompt = ''' ### Kullancı: {question} ''' input_ids = tokenizer(prompt, return_tensors="pt").input_ids output = model.generate(inputs=input_ids,max_new_tokens=512,pad_token_id=tokenizer.eos_token_id,top_k=50, do_sample=True, top_p=0.95) response = tokenizer.decode(output[0]) print(response) ``` # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_malhajar__Mistral-7B-v0.2-meditron-turkish) | Metric |Value| |---------------------------------|----:| |Avg. |63.34| |AI2 Reasoning Challenge (25-Shot)|59.56| |HellaSwag (10-Shot) |81.79| |MMLU (5-Shot) |60.35| |TruthfulQA (0-shot) |66.19| |Winogrande (5-shot) |76.24| |GSM8k (5-shot) |35.94|