Views
No views yet
| Name | Quant method | Size |
|---|---|---|
| Calme-4x7B-MoE-v0.1.Q2_K.gguf | Q2_K | 8.24GB |
| Calme-4x7B-MoE-v0.1.IQ3_XS.gguf | IQ3_XS | 9.21GB |
| Calme-4x7B-MoE-v0.1.IQ3_S.gguf | IQ3_S | 9.73GB |
| Calme-4x7B-MoE-v0.1.Q3_K_S.gguf | Q3_K_S | 9.72GB |
| Calme-4x7B-MoE-v0.1.IQ3_M.gguf | IQ3_M | 9.92GB |
| Calme-4x7B-MoE-v0.1.Q3_K.gguf | Q3_K | 10.79GB |
| Calme-4x7B-MoE-v0.1.Q3_K_M.gguf | Q3_K_M | 10.79GB |
| Calme-4x7B-MoE-v0.1.Q3_K_L.gguf | Q3_K_L | 11.68GB |
| Calme-4x7B-MoE-v0.1.IQ4_XS.gguf | IQ4_XS | 12.15GB |
| Calme-4x7B-MoE-v0.1.Q4_0.gguf | Q4_0 | 12.69GB |
| Calme-4x7B-MoE-v0.1.IQ4_NL.gguf | IQ4_NL | 12.81GB |
| Calme-4x7B-MoE-v0.1.Q4_K_S.gguf | Q4_K_S | 12.8GB |
| Calme-4x7B-MoE-v0.1.Q4_K.gguf | Q4_K | 13.61GB |
| Calme-4x7B-MoE-v0.1.Q4_K_M.gguf | Q4_K_M | 13.61GB |
| Calme-4x7B-MoE-v0.1.Q4_1.gguf | Q4_1 | 14.09GB |
| Calme-4x7B-MoE-v0.1.Q5_0.gguf | Q5_0 | 15.48GB |
| Calme-4x7B-MoE-v0.1.Q5_K_S.gguf | Q5_K_S | 15.48GB |
| Calme-4x7B-MoE-v0.1.Q5_K.gguf | Q5_K | 15.96GB |
| Calme-4x7B-MoE-v0.1.Q5_K_M.gguf | Q5_K_M | 15.96GB |
| Calme-4x7B-MoE-v0.1.Q5_1.gguf | Q5_1 | 16.88GB |
| Calme-4x7B-MoE-v0.1.Q6_K.gguf | Q6_K | 18.46GB |
| Calme-4x7B-MoE-v0.1.Q8_0.gguf | Q8_0 | 23.9GB |
1# Use a pipeline as a high-level helper
2from transformers import pipeline
3
4pipe = pipeline("text-generation", model="MaziyarPanahi/Calme-4x7B-MoE-v0.1")
5
6# Load model directly
7from transformers import AutoTokenizer, AutoModelForCausalLM
8
9tokenizer = AutoTokenizer.from_pretrained("MaziyarPanahi/Calme-4x7B-MoE-v0.1")
10model = AutoModelForCausalLM.from_pretrained("MaziyarPanahi/Calme-4x7B-MoE-v0.1")| Metric | Mistral-7B Instruct v0.2 | Calme-7B v0.1 | Calme-7B v0.2 | Calme-7B v0.3 | Calme-7B v0.4 | Calme-7B v0.5 | Calme-4x7B v0.1 | Calme-4x7B v0.2 |
|---|---|---|---|---|---|---|---|---|
| ARC | 63.14 | 67.24 | 67.75 | 67.49 | 64.85 | 67.58 | 67.15 | 76.66 |
| HellaSwag | 84.88 | 85.57 | 87.52 | 87.57 | 86.00 | 87.26 | 86.89 | 86.84 |
| TruthfulQA | 68.26 | 59.38 | 78.41 | 78.31 | 70.52 | 74.03 | 73.30 | 73.06 |
| MMLU | 60.78 | 64.97 | 61.83 | 61.93 | 62.01 | 62.04 | 62.16 | 62.16 |
| Winogrande | 77.19 | 83.35 | 82.08 | 82.32 | 79.48 | 81.85 | 80.82 | 81.06 |
| GSM8k | 40.03 | 69.29 | 73.09 | 73.09 | 77.79 | 73.54 | 74.53 | 75.66 |
Calme-7B model:| Use Case Category | Recommended Calme-7B Model | Reason |
|---|---|---|
| Educational Tools and Academic Research | Calme-7B v0.5 | Balanced performance, especially strong in TruthfulQA for accuracy and broad knowledge. |
| Commonsense Reasoning and Natural Language Apps | Calme-7B v0.2 or Calme-7B v0.3 | High performance in HellaSwag for understanding nuanced scenarios. |
| Trustworthy Information Retrieval Systems | Calme-7B v0.5 | Highest score in TruthfulQA, indicating reliable factual information provision. |
| Math Educational Software | Calme-7B v0.4 | Best performance in GSM8k, suitable for numerical reasoning and math problem-solving. |
| Context Understanding and Disambiguation | Calme-7B v0.5 | Solid performance in Winogrande, ideal for text with context and pronoun disambiguation. |
I love how GGUF democratizes the use of Large Language Models (LLMs) on commodity hardware, more specifically, personal computers without any accelerated hardware. Because of this, I am committed to converting and quantizing any models I fine-tune to make them accessible to everyone!
<s>[INST] You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.
If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.
describe about pros and cons of docker system. [/INST]<s> [INST] Mark is faster than Mary, Mary is faster than Joe. Is Joe faster than Mark? Let's think step by step [/INST]<s> [INST] explain step by step 25-4*2+3=? [/INST]<s> [INST] Vous êtes un assistant utile, respectueux et honnête. Répondez toujours de la manière la plus utile possible, tout en étant sûr. Vos réponses ne doivent inclure aucun contenu nuisible, contraire à l'éthique, raciste, sexiste, toxique, dangereux ou illégal. Assurez-vous que vos réponses sont socialement impartiales et de nature positive.
Si une question n'a pas de sens ou n'est pas cohérente d'un point de vue factuel, expliquez pourquoi au lieu de répondre quelque chose d'incorrect. Si vous ne connaissez pas la réponse à une question, veuillez ne pas partager de fausses informations.
Décrivez les avantages et les inconvénients du système Docker.[/INST]<s>[INST] Ви - корисний, поважний та чесний помічник. Завжди відповідайте максимально корисно, будучи безпечним. Ваші відповіді не повинні містити шкідливого, неетичного, расистського, сексистського, токсичного, небезпечного або нелегального контенту. Будь ласка, переконайтеся, що ваші відповіді соціально неупереджені та мають позитивний характер.
Якщо питання не має сенсу або не є фактично послідовним, поясніть чому, замість того, щоб відповідати щось некоректне. Якщо ви не знаєте відповіді на питання, будь ласка, не діліться неправдивою інформацією.
Опис про переваги та недоліки системи Docker.[/INST]