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Beagle14-7B - GGUF
- Model creator: https://huggingface.co/mlabonne/
- Original model: https://huggingface.co/mlabonne/Beagle14-7B/
Name | Quant method | Size |
---|---|---|
Beagle14-7B.Q2_K.gguf | Q2_K | 2.53GB |
Beagle14-7B.IQ3_XS.gguf | IQ3_XS | 2.81GB |
Beagle14-7B.IQ3_S.gguf | IQ3_S | 2.96GB |
Beagle14-7B.Q3_K_S.gguf | Q3_K_S | 2.95GB |
Beagle14-7B.IQ3_M.gguf | IQ3_M | 3.06GB |
Beagle14-7B.Q3_K.gguf | Q3_K | 3.28GB |
Beagle14-7B.Q3_K_M.gguf | Q3_K_M | 3.28GB |
Beagle14-7B.Q3_K_L.gguf | Q3_K_L | 3.56GB |
Beagle14-7B.IQ4_XS.gguf | IQ4_XS | 3.67GB |
Beagle14-7B.Q4_0.gguf | Q4_0 | 3.83GB |
Beagle14-7B.IQ4_NL.gguf | IQ4_NL | 3.87GB |
Beagle14-7B.Q4_K_S.gguf | Q4_K_S | 3.86GB |
Beagle14-7B.Q4_K.gguf | Q4_K | 4.07GB |
Beagle14-7B.Q4_K_M.gguf | Q4_K_M | 4.07GB |
Beagle14-7B.Q4_1.gguf | Q4_1 | 4.24GB |
Beagle14-7B.Q5_0.gguf | Q5_0 | 4.65GB |
Beagle14-7B.Q5_K_S.gguf | Q5_K_S | 4.65GB |
Beagle14-7B.Q5_K.gguf | Q5_K | 4.78GB |
Beagle14-7B.Q5_K_M.gguf | Q5_K_M | 4.78GB |
Beagle14-7B.Q5_1.gguf | Q5_1 | 5.07GB |
Beagle14-7B.Q6_K.gguf | Q6_K | 5.53GB |
Beagle14-7B.Q8_0.gguf | Q8_0 | 7.17GB |
Original model description:
license: cc-by-nc-4.0 tags: - merge - mergekit - lazymergekit - fblgit/UNA-TheBeagle-7b-v1 - argilla/distilabeled-Marcoro14-7B-slerp base_model: - fblgit/UNA-TheBeagle-7b-v1 - argilla/distilabeled-Marcoro14-7B-slerp model-index: - name: Beagle14-7B results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 72.95 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Beagle14-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 87.95 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Beagle14-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 64.7 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Beagle14-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 68.88 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Beagle14-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 82.64 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Beagle14-7B name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 71.42 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Beagle14-7B name: Open LLM Leaderboard
Beagle14-7B
Update 01/16/24: Check the DPO fine-tuned version of this model, NeuralBeagle14-7B (probably the best 7B model you can find)! π
Beagle14-7B is a merge of the following models using LazyMergekit:
π Evaluation
The evaluation was performed using LLM AutoEval on Nous suite.
Model | AGIEval | GPT4All | TruthfulQA | Bigbench | Average |
---|---|---|---|---|---|
Beagle14-7B | 44.38 | 76.53 | 69.44 | 47.25 | 59.4 |
OpenHermes-2.5-Mistral-7B | 42.75 | 72.99 | 52.99 | 40.94 | 52.42 |
NeuralHermes-2.5-Mistral-7B | 43.67 | 73.24 | 55.37 | 41.76 | 53.51 |
Nous-Hermes-2-SOLAR-10.7B | 47.79 | 74.69 | 55.92 | 44.84 | 55.81 |
Marcoro14-7B-slerp | 44.66 | 76.24 | 64.15 | 45.64 | 57.67 |
CatMarcoro14-7B-slerp | 45.21 | 75.91 | 63.81 | 47.31 | 58.06 |
𧩠Configuration
slices:
- sources:
- model: fblgit/UNA-TheBeagle-7b-v1
layer_range: [0, 32]
- model: argilla/distilabeled-Marcoro14-7B-slerp
layer_range: [0, 32]
merge_method: slerp
base_model: fblgit/UNA-TheBeagle-7b-v1
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
π» Usage
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "mlabonne/Beagle14-7B"
messages = [{"role": "user", "content": "What is a large language model?"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
Metric | Value |
---|---|
Avg. | 74.76 |
AI2 Reasoning Challenge (25-Shot) | 72.95 |
HellaSwag (10-Shot) | 87.95 |
MMLU (5-Shot) | 64.70 |
TruthfulQA (0-shot) | 68.88 |
Winogrande (5-shot) | 82.64 |
GSM8k (5-shot) | 71.42 |
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