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README.md

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+---
+license: cc-by-nc-4.0
+language:
+- ro
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+RoMistral is a family of pretrained and fine-tuned generative text models for Romanian. This is the repository for the **instruct 7B model**. Links to other models can be found at the bottom of this page.
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+OpenLLM-Ro represents the first open-source effort to build a LLM specialized for Romanian. OpenLLM-Ro developed and publicly releases a collection of Romanian LLMs, both in the form of foundational model and instruct and chat variants.
+
+
+- **Developed by:** OpenLLM-Ro
+<!-- - **Funded by [optional]:** [More Information Needed] -->
+<!-- - **Shared by [optional]:** [More Information Needed] -->
+<!-- - **Model type:** [More Information Needed] -->
+- **Language(s):** Romanian
+- **License:** cc-by-nc-4.0
+- **Finetuned from model:** [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)
+
+<!-- - **Finetuned from model [optional]:** [More Information Needed] -->
+
+### Model Sources
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** https://github.com/OpenLLM-Ro/llama-recipes
+- **Paper:** https://arxiv.org/abs/2405.07703
+
+## Intended Use
+
+### Intended Use Cases
+
+RoMistral is intented for research use in Romanian. Base models can be adapted for a variety of natural language tasks while instruction and chat tuned models are intended for assistant-like chat.
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+Use in any manner that violates the license, any applicable laws or regluations, use in languages other than Romanian.
+
+
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("OpenLLM-Ro/RoMistral-7b-Instruct")
+model = AutoModelForCausalLM.from_pretrained("OpenLLM-Ro/RoMistral-7b-Instruct")
+
+instruction = "Ce jocuri de societate pot juca cu prietenii mei?"
+chat = [
+        {"role": "user", "content": instruction},
+        ]
+prompt = tokenizer.apply_chat_template(chat, tokenize=False, system_message="")
+
+inputs = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt")
+outputs = model.generate(input_ids=inputs, max_new_tokens=128)
+print(tokenizer.decode(outputs[0]))
+```
+
+## Benchmarks
+
+| Model              | Average  | ARC      | MMLU     |Winogrande|HellaSwag | GSM8k    |TruthfulQA|
+|--------------------|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|:--------:|
+| Mistral-7B-Instruct-v0.2| 45.63    | 43.09    | 44.87    | 59.26    | 54.12    | 10.86     | **61.56**    |  
+| *RoMistral-7b-Instruct*  | ***52.49***    | ***50.39***    | ***51.64***    | ***66.69***    | ***60.24***    | ***33.71***     | 52.59    |  
+
+
+## MT-Bench
+
+| Model              | Average  | 1st turn      | 2nd turn     |
+|--------------------|:--------:|:--------:|:--------:|
+| Mistral-7B-Instruct-v0.2    | 5.84    | 6.06    | **5.63**    |
+| *RoMistral-7b-Instruct*| ***5.92***|***6.53***| *5.415* |
+
+
+
+
+## RoMistral Model Family
+
+| Model              | Link  |
+|--------------------|:--------:|
+|*RoMistral-7b-Instruct*| [link](https://huggingface.co/OpenLLM-Ro/RoMistral-7b-Instruct) |
+
+
+<!--
+## Citation 
+
+ If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section.
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]  -->

config.json

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+{
+    "_name_or_path": "mistralai/Mistral-7B-v0.1",
+    "architectures": [
+        "MistralForCausalLM"
+    ],
+    "attention_dropout": 0.0,
+    "bos_token_id": 1,
+    "eos_token_id": 2,
+    "hidden_act": "silu",
+    "hidden_size": 4096,
+    "initializer_range": 0.02,
+    "intermediate_size": 14336,
+    "max_position_embeddings": 32768,
+    "model_type": "mistral",
+    "num_attention_heads": 32,
+    "num_hidden_layers": 32,
+    "num_key_value_heads": 8,
+    "rms_norm_eps": 1e-05,
+    "rope_theta": 10000.0,
+    "sliding_window": 4096,
+    "tie_word_embeddings": false,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.40.1",
+    "use_cache": false,
+    "vocab_size": 32000,
+    "quantization_config": {
+        "quant_method": "exl2",
+        "version": "0.0.21",
+        "bits": 4.25,
+        "head_bits": 6,
+        "calibration": {
+            "rows": 100,
+            "length": 2048,
+            "dataset": "(default)"
+        }
+    }
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.40.1"
+}

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