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README.md

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+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+Hebrew-Gemma-11B-Instruct - GGUF
+- Model creator: https://huggingface.co/yam-peleg/
+- Original model: https://huggingface.co/yam-peleg/Hebrew-Gemma-11B-Instruct/
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [Hebrew-Gemma-11B-Instruct.Q2_K.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.Q2_K.gguf) | Q2_K | 3.9GB |
+| [Hebrew-Gemma-11B-Instruct.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.IQ3_XS.gguf) | IQ3_XS | 4.27GB |
+| [Hebrew-Gemma-11B-Instruct.IQ3_S.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.IQ3_S.gguf) | IQ3_S | 4.48GB |
+| [Hebrew-Gemma-11B-Instruct.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.Q3_K_S.gguf) | Q3_K_S | 4.48GB |
+| [Hebrew-Gemma-11B-Instruct.IQ3_M.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.IQ3_M.gguf) | IQ3_M | 4.63GB |
+| [Hebrew-Gemma-11B-Instruct.Q3_K.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.Q3_K.gguf) | Q3_K | 4.94GB |
+| [Hebrew-Gemma-11B-Instruct.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.Q3_K_M.gguf) | Q3_K_M | 4.94GB |
+| [Hebrew-Gemma-11B-Instruct.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.Q3_K_L.gguf) | Q3_K_L | 5.33GB |
+| [Hebrew-Gemma-11B-Instruct.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.IQ4_XS.gguf) | IQ4_XS | 5.44GB |
+| [Hebrew-Gemma-11B-Instruct.Q4_0.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.Q4_0.gguf) | Q4_0 | 5.68GB |
+| [Hebrew-Gemma-11B-Instruct.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.IQ4_NL.gguf) | IQ4_NL | 5.72GB |
+| [Hebrew-Gemma-11B-Instruct.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.Q4_K_S.gguf) | Q4_K_S | 5.72GB |
+| [Hebrew-Gemma-11B-Instruct.Q4_K.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.Q4_K.gguf) | Q4_K | 6.04GB |
+| [Hebrew-Gemma-11B-Instruct.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.Q4_K_M.gguf) | Q4_K_M | 6.04GB |
+| [Hebrew-Gemma-11B-Instruct.Q4_1.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.Q4_1.gguf) | Q4_1 | 6.25GB |
+| [Hebrew-Gemma-11B-Instruct.Q5_0.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.Q5_0.gguf) | Q5_0 | 6.81GB |
+| [Hebrew-Gemma-11B-Instruct.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.Q5_K_S.gguf) | Q5_K_S | 6.81GB |
+| [Hebrew-Gemma-11B-Instruct.Q5_K.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.Q5_K.gguf) | Q5_K | 7.0GB |
+| [Hebrew-Gemma-11B-Instruct.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.Q5_K_M.gguf) | Q5_K_M | 7.0GB |
+| [Hebrew-Gemma-11B-Instruct.Q5_1.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.Q5_1.gguf) | Q5_1 | 7.37GB |
+| [Hebrew-Gemma-11B-Instruct.Q6_K.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.Q6_K.gguf) | Q6_K | 8.01GB |
+| [Hebrew-Gemma-11B-Instruct.Q8_0.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Gemma-11B-Instruct-gguf/blob/main/Hebrew-Gemma-11B-Instruct.Q8_0.gguf) | Q8_0 | 10.37GB |
+
+
+
+
+Original model description:
+---
+license: other
+license_name: gemma-terms-of-use
+license_link: https://ai.google.dev/gemma/terms
+language:
+- en
+- he
+library_name: transformers
+---
+# Hebrew-Gemma-11B-Instruct
+
+### Base Models:
+- **07.03.2024:** [Hebrew-Gemma-11B](https://huggingface.co/yam-peleg/Hebrew-Gemma-11B)
+- **16.03.2024:** [Hebrew-Gemma-11B-V2](https://huggingface.co/yam-peleg/Hebrew-Gemma-11B-V2)
+
+### Instruct Models:
+- **07.03.2024:** [Hebrew-Gemma-11B-Instruct](https://huggingface.co/yam-peleg/Hebrew-Gemma-11B-Instruct)
+
+The Hebrew-Gemma-11B-Instruct Large Language Model (LLM) is a instruct fine-tuned version of the [Hebrew-Gemma-11B](https://huggingface.co/yam-peleg/Hebrew-Gemma-11B) generative text model using a variety of conversation datasets.
+
+It is continued pretrain of gemma-7b, extended to a larger scale and trained on 3B additional tokens of both English and Hebrew text data.
+
+
+# Instruction format
+
+This format must be strictly respected, otherwise the model will generate sub-optimal outputs.
+
+```
+<bos><start_of_turn>user
+Write a hello world program<end_of_turn>
+<start_of_turn>model
+Here is a simple hellow world program<end_of_turn><eos>
+```
+
+- The conversation starts with **`<bos>`**.
+- Each turn is preceded by a **`<start_of_turn>`** delimiter and then the role of the entity (`user` or `model`).
+- Turns finish with the **`<end_of_turn>`** token.
+- Conversation finish with the **`<eos>`** token.
+ 
+You can follow this format to build the prompt manually, if you need to do it without the tokenizer's chat template.
+
+A simple example using the tokenizer's chat template:
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_id = "Hebrew-Gemma-11B-Instruct"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, device_map="cuda")
+
+chat = [
+    { "role": "user", "content": "כתוב קוד פשוט בפייתון שמדפיס למסך את התאריך של היום" },
+]
+prompt = tokenizer.apply_chat_template(chat, tokenize=False, add_generation_prompt=True)
+```
+
+### Terms of Use
+
+As an extention of Gemma-7B, this model is subject to the original license and terms of use by Google.
+
+### Benchmark Results
+
+- Coming Soon!
+
+
+### Notice
+
+Hebrew-Gemma-11B is a pretrained base model and therefore does not have any moderation mechanisms.
+
+
+### Authors
+
+- Trained by Yam Peleg.
+- In collaboration with Jonathan Rouach and Arjeo, inc.
+