File size: 2,074 Bytes
527cc4a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
24b6054
527cc4a
4601b18
527cc4a
 
 
 
24b6054
527cc4a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
24b6054
527cc4a
 
 
 
 
 
 
24b6054
 
527cc4a
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
---
license: other
license_name: qwen-research
license_link: https://huggingface.co/Qwen/Qwen2.5-3B/blob/main/LICENSE
language:
- fr
- en
pipeline_tag: text-generation
tags:
- chat
- qwen
- qwen2.5
- finetune
- french
- english
library_name: transformers
inference: false
model_creator: MaziyarPanahi
quantized_by: MaziyarPanahi
base_model: Qwen/Qwen2.5-3B
model_name: calme-3.1-baguette-3b
datasets:
- MaziyarPanahi/french_instruct_sharegpt
- MaziyarPanahi/calme-legalkit-v0.2
---

<img src="./calme_3.png" alt="Calme-3 Models" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>

# MaziyarPanahi/calme-3.1-baguette-3b

This model is an advanced iteration of the powerful Qwen/Qwen2.5-3B, fine-tuned specifically to enhance its capabilities across general domains in both French and English.


# ⚡ Quantized GGUF

All GGUF models are available here: [MaziyarPanahi/calme-3.1-baguette-3b-GGUF](https://huggingface.co/MaziyarPanahi/calme-3.1-baguette-3b-GGUF)


# 🏆 [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)

Leaderboard 2 coming soon!


# Prompt Template

This model uses `ChatML` prompt template:

```
<|im_start|>system
{System}
<|im_end|>
<|im_start|>user
{User}
<|im_end|>
<|im_start|>assistant
{Assistant}
````

# How to use


```python

# Use a pipeline as a high-level helper

from transformers import pipeline

messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe = pipeline("text-generation", model="MaziyarPanahi/calme-3.1-baguette-3b")
pipe(messages)


# Load model directly

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("MaziyarPanahi/calme-3.1-baguette-3b")
model = AutoModelForCausalLM.from_pretrained("MaziyarPanahi/calme-3.1-baguette-3b")
```



# Ethical Considerations

As with any large language model, users should be aware of potential biases and limitations. We recommend implementing appropriate safeguards and human oversight when deploying this model in production environments.