Quantization made by Richard Erkhov.

[Github](https://github.com/RichardErkhov)

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Hebrew-Mistral-7B - GGUF
- Model creator: https://huggingface.co/yam-peleg/
- Original model: https://huggingface.co/yam-peleg/Hebrew-Mistral-7B/


| Name | Quant method | Size |
| ---- | ---- | ---- |
| [Hebrew-Mistral-7B.Q2_K.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.Q2_K.gguf) | Q2_K | 2.67GB |
| [Hebrew-Mistral-7B.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.IQ3_XS.gguf) | IQ3_XS | 2.96GB |
| [Hebrew-Mistral-7B.IQ3_S.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.IQ3_S.gguf) | IQ3_S | 3.12GB |
| [Hebrew-Mistral-7B.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.Q3_K_S.gguf) | Q3_K_S | 3.1GB |
| [Hebrew-Mistral-7B.IQ3_M.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.IQ3_M.gguf) | IQ3_M | 3.21GB |
| [Hebrew-Mistral-7B.Q3_K.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.Q3_K.gguf) | Q3_K | 3.43GB |
| [Hebrew-Mistral-7B.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.Q3_K_M.gguf) | Q3_K_M | 3.43GB |
| [Hebrew-Mistral-7B.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.Q3_K_L.gguf) | Q3_K_L | 3.71GB |
| [Hebrew-Mistral-7B.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.IQ4_XS.gguf) | IQ4_XS | 3.84GB |
| [Hebrew-Mistral-7B.Q4_0.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.Q4_0.gguf) | Q4_0 | 4.0GB |
| [Hebrew-Mistral-7B.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.IQ4_NL.gguf) | IQ4_NL | 4.04GB |
| [Hebrew-Mistral-7B.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.Q4_K_S.gguf) | Q4_K_S | 4.03GB |
| [Hebrew-Mistral-7B.Q4_K.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.Q4_K.gguf) | Q4_K | 4.24GB |
| [Hebrew-Mistral-7B.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.Q4_K_M.gguf) | Q4_K_M | 4.24GB |
| [Hebrew-Mistral-7B.Q4_1.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.Q4_1.gguf) | Q4_1 | 4.42GB |
| [Hebrew-Mistral-7B.Q5_0.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.Q5_0.gguf) | Q5_0 | 4.84GB |
| [Hebrew-Mistral-7B.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.Q5_K_S.gguf) | Q5_K_S | 4.84GB |
| [Hebrew-Mistral-7B.Q5_K.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.Q5_K.gguf) | Q5_K | 4.96GB |
| [Hebrew-Mistral-7B.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.Q5_K_M.gguf) | Q5_K_M | 4.96GB |
| [Hebrew-Mistral-7B.Q5_1.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.Q5_1.gguf) | Q5_1 | 5.26GB |
| [Hebrew-Mistral-7B.Q6_K.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.Q6_K.gguf) | Q6_K | 5.74GB |
| [Hebrew-Mistral-7B.Q8_0.gguf](https://huggingface.co/RichardErkhov/yam-peleg_-_Hebrew-Mistral-7B-gguf/blob/main/Hebrew-Mistral-7B.Q8_0.gguf) | Q8_0 | 7.43GB |




Original model description:
---
license: apache-2.0
language:
- en
- he
library_name: transformers
---
# Hebrew-Mistral-7B

Hebrew-Mistral-7B is an open-source Large Language Model (LLM) pretrained in hebrew and english pretrained with 7B billion parameters, based on Mistral-7B-v1.0 from Mistral.

It has an extended hebrew tokenizer with 64,000 tokens and is continuesly pretrained from Mistral-7B on tokens in both English and Hebrew.

The resulting model is a powerful general-purpose language model suitable for a wide range of natural language processing tasks, with a focus on Hebrew language understanding and generation.

### Usage

Below are some code snippets on how to get quickly started with running the model.

First make sure to `pip install -U transformers`, then copy the snippet from the section that is relevant for your usecase.

### Running on CPU

```python
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("yam-peleg/Hebrew-Mistral-7B")
model = AutoModelForCausalLM.from_pretrained("yam-peleg/Hebrew-Mistral-7B")

input_text = "שלום! מה שלומך היום?"
input_ids = tokenizer(input_text, return_tensors="pt")

outputs = model.generate(**input_ids)
print(tokenizer.decode(outputs[0]))
```

### Running on GPU

```python
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("yam-peleg/Hebrew-Mistral-7B")
model = AutoModelForCausalLM.from_pretrained("yam-peleg/Hebrew-Mistral-7B", device_map="auto")

input_text = "שלום! מה שלומך היום?"
input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")

outputs = model.generate(**input_ids)
print(tokenizer.decode(outputs[0]))
```

### Running with 4-Bit precision

```python
from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig

tokenizer = AutoTokenizer.from_pretrained("yam-peleg/Hebrew-Mistral-7B")
model = AutoModelForCausalLM.from_pretrained("yam-peleg/Hebrew-Mistral-7B", quantization_config = BitsAndBytesConfig(load_in_4bit=True))

input_text = "שלום! מה שלומך היום?"
input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")

outputs = model.generate(**input_ids)
print(tokenizer.decode(outputs[0])
```

### Notice

Hebrew-Mistral-7B 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.