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mhenrichsen_-_hestenettetLM-gguf
RichardErkhov/mhenrichsen_-_hestenettetLM-gguf
mhenrichsen_-_hestenettetLM-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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.gguf92.8 GB · 100%
At a glance
- Access
- Public
- Created
- Sep 2, 2024
- Updated
- Sep 2, 2024
- SHA
- 13324252
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
hestenettetLM - GGUF
- Model creator: https://huggingface.co/mhenrichsen/
- Original model: https://huggingface.co/mhenrichsen/hestenettetLM/
| Name | Quant method | Size |
|---|---|---|
| hestenettetLM.Q2_K.gguf | Q2_K | 2.09GB |
| hestenettetLM.IQ3_XS.gguf | IQ3_XS | 2.81GB |
| hestenettetLM.IQ3_S.gguf | IQ3_S | 2.96GB |
| hestenettetLM.Q3_K_S.gguf | Q3_K_S | 2.95GB |
| hestenettetLM.IQ3_M.gguf | IQ3_M | 3.06GB |
| hestenettetLM.Q3_K.gguf | Q3_K | 3.28GB |
| hestenettetLM.Q3_K_M.gguf | Q3_K_M | 3.28GB |
| hestenettetLM.Q3_K_L.gguf | Q3_K_L | 3.56GB |
| hestenettetLM.IQ4_XS.gguf | IQ4_XS | 3.67GB |
| hestenettetLM.Q4_0.gguf | Q4_0 | 3.83GB |
| hestenettetLM.IQ4_NL.gguf | IQ4_NL | 3.87GB |
| hestenettetLM.Q4_K_S.gguf | Q4_K_S | 2.02GB |
| hestenettetLM.Q4_K.gguf | Q4_K | 4.07GB |
| hestenettetLM.Q4_K_M.gguf | Q4_K_M | 4.07GB |
| hestenettetLM.Q4_1.gguf | Q4_1 | 4.24GB |
| hestenettetLM.Q5_0.gguf | Q5_0 | 4.65GB |
| hestenettetLM.Q5_K_S.gguf | Q5_K_S | 4.65GB |
| hestenettetLM.Q5_K.gguf | Q5_K | 4.78GB |
| hestenettetLM.Q5_K_M.gguf | Q5_K_M | 4.78GB |
| hestenettetLM.Q5_1.gguf | Q5_1 | 5.07GB |
| hestenettetLM.Q6_K.gguf | Q6_K | 5.53GB |
| hestenettetLM.Q8_0.gguf | Q8_0 | 7.17GB |
Original model description:
license: mit datasets:
- mhenrichsen/hestenettet language:
- da
HestenettetLM
En dansk LLM trænet på hele hestenettet over 3 epoker.
Modellen er baseret på Mistral 7b, og har et kontekstvindue på 8k.
from transformers import AutoTokenizer, TextStreamer, AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("mhenrichsen/hestenettetLM")
tokenizer = AutoTokenizer.from_pretrained("mhenrichsen/hestenettetLM")
streamer = TextStreamer(tokenizer, skip_special_tokens=True)
tokens = tokenizer(
"Den bedste hest er en ",
return_tensors='pt'
)['input_ids']
# Generate output
generation_output = model.generate(
tokens,
streamer=streamer,
max_length = 8194,
)
Eksempel: "Den bedste hest er en " bliver til: "Den bedste hest er en veltrænet hest."
- Created
- Sep 2, 2024
- Updated
- Sep 2, 2024