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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
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pythia-160m-seed2 - bnb 8bits
- Model creator: https://huggingface.co/EleutherAI/
- Original model: https://huggingface.co/E... | {} | RichardErkhov/EleutherAI_-_pythia-160m-seed2-8bits | null | [
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"gpt_neox",
"text-generation",
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"endpoints_compatible",
"text-generation-inference",
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"region:us"
] | null | 2024-04-23T07:58:17+00:00 | [] | [] | TAGS
#transformers #safetensors #gpt_neox #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
pythia-160m-seed2 - bnb 8bits
- Model creator: URL
- Original model: URL
Original model description:
Entry not found
| [] | [
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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
pythia-160m-seed3 - bnb 4bits
- Model creator: https://huggingface.co/EleutherAI/
- Original model: https://huggingface.co/E... | {} | RichardErkhov/EleutherAI_-_pythia-160m-seed3-4bits | null | [
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#transformers #safetensors #gpt_neox #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
pythia-160m-seed3 - bnb 4bits
- Model creator: URL
- Original model: URL
Original model description:
Entry not found
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"TAGS\n#transformers #safetensors #gpt_neox #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us \n"
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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
pythia-14m - bnb 4bits
- Model creator: https://huggingface.co/EleutherAI/
- Original model: https://huggingface.co/Eleuther... | {} | RichardErkhov/EleutherAI_-_pythia-14m-4bits | null | [
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"gpt_neox",
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] | null | 2024-04-23T07:59:13+00:00 | [] | [] | TAGS
#transformers #safetensors #gpt_neox #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
| Quantization made by Richard Erkhov.
Github
Discord
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pythia-14m - bnb 4bits
- Model creator: URL
- Original model: URL
Original model description:
Entry not found
| [] | [
"TAGS\n#transformers #safetensors #gpt_neox #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us \n"
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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
pythia-14m - bnb 8bits
- Model creator: https://huggingface.co/EleutherAI/
- Original model: https://huggingface.co/Eleuther... | {} | RichardErkhov/EleutherAI_-_pythia-14m-8bits | null | [
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"text-generation",
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#transformers #safetensors #gpt_neox #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us
| Quantization made by Richard Erkhov.
Github
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Request more models
pythia-14m - bnb 8bits
- Model creator: URL
- Original model: URL
Original model description:
Entry not found
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"TAGS\n#transformers #safetensors #gpt_neox #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us \n"
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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
pythia-160m-seed3 - bnb 8bits
- Model creator: https://huggingface.co/EleutherAI/
- Original model: https://huggingface.co/E... | {} | RichardErkhov/EleutherAI_-_pythia-160m-seed3-8bits | null | [
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"safetensors",
"gpt_neox",
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#transformers #safetensors #gpt_neox #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
pythia-160m-seed3 - bnb 8bits
- Model creator: URL
- Original model: URL
Original model description:
Entry not found
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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
pythia-1b - bnb 4bits
- Model creator: https://huggingface.co/EleutherAI/
- Original model: https://huggingface.co/EleutherA... | {} | RichardErkhov/EleutherAI_-_pythia-1b-4bits | null | [
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"endpoints_compatible",
"text-generation-inference",
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"region:us"
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| Quantization made by Richard Erkhov.
Github
Discord
Request more models
pythia-1b - bnb 4bits
* Model creator: URL
* Original model: URL
Original model description:
---------------------------
language:
* en
tags:
* pytorch
* causal-lm
* pythia
license: apache-2.0
datasets:
* the\_pile
---
The *Py... | [
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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
pythia-31m - bnb 4bits
- Model creator: https://huggingface.co/EleutherAI/
- Original model: https://huggingface.co/Eleuther... | {} | RichardErkhov/EleutherAI_-_pythia-31m-4bits | null | [
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"gpt_neox",
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"endpoints_compatible",
"text-generation-inference",
"4-bit",
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] | null | 2024-04-23T08:00:19+00:00 | [] | [] | TAGS
#transformers #safetensors #gpt_neox #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
pythia-31m - bnb 4bits
- Model creator: URL
- Original model: URL
Original model description:
Entry not found
| [] | [
"TAGS\n#transformers #safetensors #gpt_neox #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us \n"
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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
pythia-31m - bnb 8bits
- Model creator: https://huggingface.co/EleutherAI/
- Original model: https://huggingface.co/Eleuther... | {} | RichardErkhov/EleutherAI_-_pythia-31m-8bits | null | [
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#transformers #safetensors #gpt_neox #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
pythia-31m - bnb 8bits
- Model creator: URL
- Original model: URL
Original model description:
Entry not found
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"TAGS\n#transformers #safetensors #gpt_neox #text-generation #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us \n"
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** ... | {"library_name": "peft", "base_model": "meta-llama/Meta-Llama-3-8B-Instruct"} | shivanikerai/Meta-Llama-3-8B-Instruct-adapter-title-suggestion-v1.0 | null | [
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"arxiv:1910.09700",
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"region:us"
] | null | 2024-04-23T08:02:04+00:00 | [
"1910.09700"
] | [] | TAGS
#peft #arxiv-1910.09700 #base_model-meta-llama/Meta-Llama-3-8B-Instruct #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Funded by [optional]:
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- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
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image-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-tiny-patch4-window7-224-finetuned-ddc
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https:... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/swin-tiny-patch4-window7-224", "model-index": [{"name": "swin-tiny-patch4-window7-224-finetuned-ddc", "results": [{"task": {"type": "image-classification", "name": "Image Classifi... | iayrots/swin-tiny-patch4-window7-224-finetuned-ddc | null | [
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| swin-tiny-patch4-window7-224-finetuned-ddc
==========================================
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0101
* Accuracy: 0.9946
Model description
--------------... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | EpicJhon/llama_224 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
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- Shared by [optional]:
- Model type:
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- License... | [
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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
pythia-1b - bnb 8bits
- Model creator: https://huggingface.co/EleutherAI/
- Original model: https://huggingface.co/EleutherA... | {} | RichardErkhov/EleutherAI_-_pythia-1b-8bits | null | [
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"2304.01373",
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| Quantization made by Richard Erkhov.
Github
Discord
Request more models
pythia-1b - bnb 8bits
* Model creator: URL
* Original model: URL
Original model description:
---------------------------
language:
* en
tags:
* pytorch
* causal-lm
* pythia
license: apache-2.0
datasets:
* the\_pile
---
The *Py... | [
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text-generation | transformers |
# suzume-linear1
suzume-linear1 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [alfredplpl/suzume-poc](https://huggingface.co/alfredplpl/suzume-poc)
* [alpindale/gemma-2b-it](https://huggingface.co/alpindale/gemma-2b-it... | {"tags": ["merge", "mergekit", "lazymergekit", "alfredplpl/suzume-poc", "alpindale/gemma-2b-it"], "base_model": ["alfredplpl/suzume-poc", "alpindale/gemma-2b-it"]} | aipib/suzume-linear1 | null | [
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"base_model:alpindale/gemma-2b-it",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inferen... | null | 2024-04-23T08:05:07+00:00 | [] | [] | TAGS
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|
# suzume-linear1
suzume-linear1 is a merge of the following models using LazyMergekit:
* alfredplpl/suzume-poc
* alpindale/gemma-2b-it
## Configuration
## Usage
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"## Usage"
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# results_bertweet
This model is a fine-tuned version of [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) on an u... | {"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "base_model": "vinai/bertweet-base", "model-index": [{"name": "results_bertweet", "results": []}]} | dianamihalache27/results_bertweet | null | [
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|
# results_bertweet
This model is a fine-tuned version of vinai/bertweet-base on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6385
- Accuracy: 0.7839
- F1: 0.4898
## Model description
More information needed
## Intended uses & limitations
More information needed
## Trai... | [
"# results_bertweet\n\nThis model is a fine-tuned version of vinai/bertweet-base on an unknown dataset.\nIt achieves the following results on the evaluation set:\n- Loss: 0.6385\n- Accuracy: 0.7839\n- F1: 0.4898",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore informa... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/featherlite-ai/Featherlite-Vicuna-13B-chat
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If t... | {"language": ["en"], "license": "llama2", "library_name": "transformers", "base_model": "featherlite-ai/Featherlite-Vicuna-13B-chat", "quantized_by": "mradermacher"} | mradermacher/Featherlite-Vicuna-13B-chat-GGUF | null | [
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#transformers #gguf #en #base_model-featherlite-ai/Featherlite-Vicuna-13B-chat #license-llama2 #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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text-generation | transformers |
## Model Details
Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available open source c... | {"language": ["en"], "license": "other", "tags": ["facebook", "meta", "pytorch", "llama", "llama-3"], "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE", "extra_gated_prompt": "### META LLAMA 3 COMMUNITY LICENSE AGREEMENT\nMeta Llama 3 Version Release Date: April 18, 2024\n\"Agreemen... | ISTA-DASLab/Meta-Llama-3-8B-Instruct | null | [
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| Model Details
-------------
Meta developed and released the Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available op... | [
"### Use with transformers\n\n\nYou can run conversational inference using the Transformers pipeline abstraction, or by leveraging the Auto classes with the 'generate()' function. Let's see examples of both.",
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"#### Transformers AutoModelForCausalLM",
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | lilucheng/llamatest | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": ["unsloth", "trl", "sft"]} | AnonY0324/llama2-4bit | null | [
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# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
Mistral-7B-v0.1-population-first-ft - bnb 4bits
- Model creator: https://huggingface.co/EleutherAI/
- Original model: https:... | {} | RichardErkhov/EleutherAI_-_Mistral-7B-v0.1-population-first-ft-4bits | null | [
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#transformers #safetensors #mistral #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
Mistral-7B-v0.1-population-first-ft - bnb 4bits
- Model creator: URL
- Original model: URL
Original model description:
---
library_name: transformers
tags: []
---
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** ... | {"library_name": "peft", "base_model": "Trelis/Llama-2-7b-chat-hf-sharded-bf16"} | Vibhav1612/LlamaStories30Epoches | null | [
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text-generation | null | # GGUFs of Llama-3-8B-16K
GGUF conversion and quantization of https://huggingface.co/mattshumer/Llama-3-8B-16K
Done with Maxime Labonne's AutoGGUF
## Orginal model card
This is an extended (16K) context version of LLaMA 3 8B (base, not instruct). Trained for five hours on 8x A6000 GPUs, using the `Yukang/LongAlpaca-1... | {"language": ["en"], "license": "other", "tags": ["facebook", "meta", "llama", "llama-3", "GGUF"], "datasets": ["Yukang/LongAlpaca-16k-length"], "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE"} | olafgeibig/Llama-3-8B-16K-GGUF | null | [
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| # GGUFs of Llama-3-8B-16K
GGUF conversion and quantization of URL
Done with Maxime Labonne's AutoGGUF
## Orginal model card
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text-generation | transformers | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
Mistral-7B-v0.1-population-first-ft - bnb 8bits
- Model creator: https://huggingface.co/EleutherAI/
- Original model: https:... | {} | RichardErkhov/EleutherAI_-_Mistral-7B-v0.1-population-first-ft-8bits | null | [
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#transformers #safetensors #mistral #text-generation #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
Mistral-7B-v0.1-population-first-ft - bnb 8bits
- Model creator: URL
- Original model: URL
Original model description:
---
library_name: transformers
tags: []
---
# Model Card for Model ID
## Model Details
### Model Description
T... | [
"# Model Card for Model ID",
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text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# kalai_bert_model_test_4_out
This model is a fine-tuned version of [KalaiselvanD/kalai_bert_model_test_4_out](https://huggingface... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "KalaiselvanD/kalai_bert_model_test_4_out", "model-index": [{"name": "kalai_bert_model_test_4_out", "results": []}]} | KalaiselvanD/kalai_bert_model_test_4_out | null | [
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| kalai\_bert\_model\_test\_4\_out
================================
This model is a fine-tuned version of KalaiselvanD/kalai\_bert\_model\_test\_4\_out on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1363
* Accuracy: 1.0
Model description
-----------------
More information ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
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feature-extraction | transformers |
# megatron.bert-base.bpe-64k-no_pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done f... | {"language": ["sv"]} | KBLab/megatron.bert-base.bpe-64k-no_pretok.25k-steps | null | [
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|
# URL-64k-no_pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 25k training ste... | [
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null | transformers |
# hus960/Unsafe-Llama-3-8B-Q4_K_M-GGUF
This model was converted to GGUF format from [`vicgalle/Unsafe-Llama-3-8B`](https://huggingface.co/vicgalle/Unsafe-Llama-3-8B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://h... | {"license": "apache-2.0", "library_name": "transformers", "tags": ["llama-cpp", "gguf-my-repo"], "datasets": ["vicgalle/configurable-system-prompt-multitask"]} | hus960/Unsafe-Llama-3-8B-Q4_K_M-GGUF | null | [
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|
# hus960/Unsafe-Llama-3-8B-Q4_K_M-GGUF
This model was converted to GGUF format from 'vicgalle/Unsafe-Llama-3-8B' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.
CLI:
Server:
... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | JFernandoGRE/falcon7binstruct_augmenteddemocracy_dups_all4_gender | null | [
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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feature-extraction | transformers |
# megatron.bert-base.spe-bpe-32k-no_pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was do... | {"language": ["sv"]} | KBLab/megatron.bert-base.spe-bpe-32k-no_pretok.25k-steps | null | [
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# URL-bpe-32k-no_pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 25k training... | [
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Info... | {"library_name": "peft", "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0"} | bmehrba/TinyLlama-1.1B-Chat-v1.0-fine-tuned-adapters_Epistemic_tiny_0.8_Seed103 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
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- Language(s) (NLP):
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- Finetuned from model [optional]:
### Model Sources [optional]
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Info... | {"library_name": "peft", "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0"} | bmehrba/TinyLlama-1.1B-Chat-v1.0-fine-tuned_Epistemic_tiny_0.8_Seed103 | null | [
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# Model Card for Model ID
## Model Details
### Model Description
- Developed by:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License:
- Finetuned from model [optional]:
### Model Sources [optional]
- Repository:
- Paper [optional]:
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null | null | Quantization made by Richard Erkhov.
[Github](https://github.com/RichardErkhov)
[Discord](https://discord.gg/pvy7H8DZMG)
[Request more models](https://github.com/RichardErkhov/quant_request)
Mistral-7B-v0.1-population-first-ft - GGUF
- Model creator: https://huggingface.co/EleutherAI/
- Original model: https://hug... | {} | RichardErkhov/EleutherAI_-_Mistral-7B-v0.1-population-first-ft-gguf | null | [
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"1910.09700"
] | [] | TAGS
#gguf #arxiv-1910.09700 #region-us
| Quantization made by Richard Erkhov.
Github
Discord
Request more models
Mistral-7B-v0.1-population-first-ft - GGUF
* Model creator: URL
* Original model: URL
Name: Mistral-7B-v0.1-population-first-ft.Q2\_K.gguf, Quant method: Q2\_K, Size: 2.53GB
Name: Mistral-7B-v0.1-population-first-ft.IQ3\_XS.gguf, Quant ... | [
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feature-extraction | transformers |
# megatron.bert-base.spe-bpe-32k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done ... | {"language": ["sv"]} | KBLab/megatron.bert-base.spe-bpe-32k-pretok.25k-steps | null | [
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# URL-bpe-32k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 25k training st... | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": ["trl", "dpo"]} | NBA55/Experiment_with_trained_model_Final_DPO_for_all_3_issues-epoch-2-with-token-size-2048 | null | [
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|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
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"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s)... | [
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feature-extraction | transformers |
# megatron.bert-base.spe-bpe-64k-no_pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was do... | {"language": ["sv"]} | KBLab/megatron.bert-base.spe-bpe-64k-no_pretok.25k-steps | null | [
"transformers",
"safetensors",
"megatron-bert",
"feature-extraction",
"sv",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:21:06+00:00 | [] | [
"sv"
] | TAGS
#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us
|
# URL-bpe-64k-no_pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 25k training... | [
"# URL-bpe-64k-no_pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.\n\nTraining was done for 25... | [
"TAGS\n#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us \n",
"# URL-bpe-64k-no_pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mos... | [
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"TAGS\n#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us \n# URL-bpe-64k-no_pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of... |
feature-extraction | transformers |
# megatron.bert-base.spe-bpe-64k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done ... | {"language": ["sv"]} | KBLab/megatron.bert-base.spe-bpe-64k-pretok.25k-steps | null | [
"transformers",
"safetensors",
"megatron-bert",
"feature-extraction",
"sv",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:21:41+00:00 | [] | [
"sv"
] | TAGS
#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us
|
# URL-bpe-64k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 25k training st... | [
"# URL-bpe-64k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.\n\nTraining was done for 25k t... | [
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"# URL-bpe-64k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly... | [
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text-generation | null |
# hus960/Llama-3-8b.UNLEASHED-Q4_K_M-GGUF
This model was converted to GGUF format from [`raincandy-u/Llama-3-8b.UNLEASHED`](https://huggingface.co/raincandy-u/Llama-3-8b.UNLEASHED) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model ... | {"language": ["en"], "license": "other", "tags": ["facebook", "meta", "pytorch", "llama", "llama-3", "llama-cpp", "gguf-my-repo"], "datasets": ["unalignment/toxic-dpo-v0.2"], "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE"} | hus960/Llama-3-8b.UNLEASHED-Q4_K_M-GGUF | null | [
"gguf",
"facebook",
"meta",
"pytorch",
"llama",
"llama-3",
"llama-cpp",
"gguf-my-repo",
"text-generation",
"en",
"dataset:unalignment/toxic-dpo-v0.2",
"license:other",
"region:us"
] | null | 2024-04-23T08:21:57+00:00 | [] | [
"en"
] | TAGS
#gguf #facebook #meta #pytorch #llama #llama-3 #llama-cpp #gguf-my-repo #text-generation #en #dataset-unalignment/toxic-dpo-v0.2 #license-other #region-us
|
# hus960/Llama-3-8b.UNLEASHED-Q4_K_M-GGUF
This model was converted to GGUF format from 'raincandy-u/Llama-3-8b.UNLEASHED' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.
CLI:
S... | [
"# hus960/Llama-3-8b.UNLEASHED-Q4_K_M-GGUF\nThis model was converted to GGUF format from 'raincandy-u/Llama-3-8b.UNLEASHED' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
"## Use with URL\n\nInstall URL through brew.\n\n\nInvoke the URL server or the... | [
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feature-extraction | transformers |
# megatron.bert-base.unigram-32k-no_pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was do... | {"language": ["sv"]} | KBLab/megatron.bert-base.unigram-32k-no_pretok.25k-steps | null | [
"transformers",
"safetensors",
"megatron-bert",
"feature-extraction",
"sv",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:22:17+00:00 | [] | [
"sv"
] | TAGS
#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us
|
# URL-base.unigram-32k-no_pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 25k... | [
"# URL-base.unigram-32k-no_pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.\n\nTraining was do... | [
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feature-extraction | transformers |
# megatron.bert-base.unigram-32k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done ... | {"language": ["sv"]} | KBLab/megatron.bert-base.unigram-32k-pretok.25k-steps | null | [
"transformers",
"safetensors",
"megatron-bert",
"feature-extraction",
"sv",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:22:54+00:00 | [] | [
"sv"
] | TAGS
#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us
|
# URL-base.unigram-32k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 25k tr... | [
"# URL-base.unigram-32k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.\n\nTraining was done ... | [
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feature-extraction | transformers |
# megatron.bert-base.unigram-64k-no_pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was do... | {"language": ["sv"]} | KBLab/megatron.bert-base.unigram-64k-no_pretok.25k-steps | null | [
"transformers",
"safetensors",
"megatron-bert",
"feature-extraction",
"sv",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:23:26+00:00 | [] | [
"sv"
] | TAGS
#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us
|
# URL-base.unigram-64k-no_pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 25k... | [
"# URL-base.unigram-64k-no_pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.\n\nTraining was do... | [
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text-generation | transformers | Quantizations of https://huggingface.co/stabilityai/stable-code-instruct-3b
# From original readme
## Usage
Here's how you can run the model use the model:
```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("stabilityai/stable-code-instruct-... | {"language": ["en"], "license": "other", "tags": ["transformers", "stabilityai", "gguf", "imatrix", "stable-code-instruct-3b"], "inference": false, "pipeline_tag": "text-generation"} | duyntnet/stable-code-instruct-3b-imatrix-GGUF | null | [
"transformers",
"gguf",
"stabilityai",
"imatrix",
"stable-code-instruct-3b",
"text-generation",
"en",
"license:other",
"region:us"
] | null | 2024-04-23T08:23:53+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #stabilityai #imatrix #stable-code-instruct-3b #text-generation #en #license-other #region-us
| Quantizations of URL
# From original readme
## Usage
Here's how you can run the model use the model:
''' | [
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"## Usage\nHere's how you can run the model use the model:\n\n\n'''"
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] |
feature-extraction | transformers |
# megatron.bert-base.unigram-64k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done ... | {"language": ["sv"]} | KBLab/megatron.bert-base.unigram-64k-pretok.25k-steps | null | [
"transformers",
"safetensors",
"megatron-bert",
"feature-extraction",
"sv",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:23:59+00:00 | [] | [
"sv"
] | TAGS
#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us
|
# URL-base.unigram-64k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 25k tr... | [
"# URL-base.unigram-64k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.\n\nTraining was done ... | [
"TAGS\n#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us \n",
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feature-extraction | transformers |
# megatron.bert-base.wordpiece-32k-no_pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was ... | {"language": ["sv"]} | KBLab/megatron.bert-base.wordpiece-32k-no_pretok.25k-steps | null | [
"transformers",
"safetensors",
"megatron-bert",
"feature-extraction",
"sv",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:24:38+00:00 | [] | [
"sv"
] | TAGS
#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us
|
# URL-base.wordpiece-32k-no_pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 2... | [
"# URL-base.wordpiece-32k-no_pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.\n\nTraining was ... | [
"TAGS\n#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us \n",
"# URL-base.wordpiece-32k-no_pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, con... | [
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"TAGS\n#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us \n# URL-base.wordpiece-32k-no_pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consistin... |
null | null |
# hus960/Llama-3-SLERP-8B-Q4_K_M-GGUF
This model was converted to GGUF format from [`mlabonne/Llama-3-SLERP-8B`](https://huggingface.co/mlabonne/Llama-3-SLERP-8B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://hugg... | {"license": "other", "tags": ["merge", "mergekit", "lazymergekit", "llama-cpp", "gguf-my-repo"], "base_model": ["meta-llama/Meta-Llama-3-8B", "meta-llama/Meta-Llama-3-8B-Instruct"]} | hus960/Llama-3-SLERP-8B-Q4_K_M-GGUF | null | [
"gguf",
"merge",
"mergekit",
"lazymergekit",
"llama-cpp",
"gguf-my-repo",
"base_model:meta-llama/Meta-Llama-3-8B",
"base_model:meta-llama/Meta-Llama-3-8B-Instruct",
"license:other",
"region:us"
] | null | 2024-04-23T08:25:00+00:00 | [] | [] | TAGS
#gguf #merge #mergekit #lazymergekit #llama-cpp #gguf-my-repo #base_model-meta-llama/Meta-Llama-3-8B #base_model-meta-llama/Meta-Llama-3-8B-Instruct #license-other #region-us
|
# hus960/Llama-3-SLERP-8B-Q4_K_M-GGUF
This model was converted to GGUF format from 'mlabonne/Llama-3-SLERP-8B' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.
CLI:
Server:
N... | [
"# hus960/Llama-3-SLERP-8B-Q4_K_M-GGUF\nThis model was converted to GGUF format from 'mlabonne/Llama-3-SLERP-8B' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
"## Use with URL\n\nInstall URL through brew.\n\n\nInvoke the URL server or the CLI.\n\nCL... | [
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feature-extraction | transformers |
# megatron.bert-base.wordpiece-32k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was don... | {"language": ["sv"]} | KBLab/megatron.bert-base.wordpiece-32k-pretok.25k-steps | null | [
"transformers",
"safetensors",
"megatron-bert",
"feature-extraction",
"sv",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:25:08+00:00 | [] | [
"sv"
] | TAGS
#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us
|
# URL-base.wordpiece-32k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 25k ... | [
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text-generation | transformers |
# Gemma 2B Translation v0.122
- Eval Loss: `0.45365`
- Train Loss: `0.43420`
- lr: `6e-05`
- optimizer: adamw
- lr_scheduler_type: cosine
## Prompt Template
```
<bos>##English##
Hamsters don't eat cats.
##Korean##
햄스터는 고양이를 먹지 않습니다.<eos>
```
```
<bos>##Korean##
햄스터는 고양이를 먹지 않습니다.
##English##
Hamsters do no... | {"language": ["ko"], "license": "gemma", "library_name": "transformers", "tags": ["gemma", "pytorch", "instruct", "finetune", "translation"], "datasets": ["traintogpb/aihub-flores-koen-integrated-sparta-30k"], "widget": [{"messages": [{"role": "user", "content": "Hamsters don't eat cats."}]}], "base_model": "beomi/gemm... | lemon-mint/gemma-2b-translation-v0.122 | null | [
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"base_model:beomi/gemma-ko-2b",
"license:gemma",
"autotrain_compatible",
"endpoints_compatibl... | null | 2024-04-23T08:25:27+00:00 | [] | [
"ko"
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|
# Gemma 2B Translation v0.122
- Eval Loss: '0.45365'
- Train Loss: '0.43420'
- lr: '6e-05'
- optimizer: adamw
- lr_scheduler_type: cosine
## Prompt Template
## Model Description
- Developed by: 'lemon-mint'
- Model type: Gemma
- Language(s) (NLP): English
- License: gemma-terms-of-use
- Finetuned from model:... | [
"# Gemma 2B Translation v0.122\n\n- Eval Loss: '0.45365'\n- Train Loss: '0.43420'\n- lr: '6e-05'\n- optimizer: adamw\n- lr_scheduler_type: cosine",
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feature-extraction | transformers |
# megatron.bert-base.wordpiece-64k-no_pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was ... | {"language": ["sv"]} | KBLab/megatron.bert-base.wordpiece-64k-no_pretok.25k-steps | null | [
"transformers",
"safetensors",
"megatron-bert",
"feature-extraction",
"sv",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:25:38+00:00 | [] | [
"sv"
] | TAGS
#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us
|
# URL-base.wordpiece-64k-no_pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 2... | [
"# URL-base.wordpiece-64k-no_pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.\n\nTraining was ... | [
"TAGS\n#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us \n",
"# URL-base.wordpiece-64k-no_pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, con... | [
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feature-extraction | transformers |
# megatron.bert-base.wordpiece-64k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was don... | {"language": ["sv"]} | KBLab/megatron.bert-base.wordpiece-64k-pretok.25k-steps | null | [
"transformers",
"safetensors",
"megatron-bert",
"feature-extraction",
"sv",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:26:13+00:00 | [] | [
"sv"
] | TAGS
#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us
|
# URL-base.wordpiece-64k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 25k ... | [
"# URL-base.wordpiece-64k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.\n\nTraining was don... | [
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"# URL-base.wordpiece-64k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consis... | [
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"TAGS\n#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us \n# URL-base.wordpiece-64k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting m... |
null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Saiga_timelist_task100steps
This model is a fine-tuned version of [TheBloke/Llama-2-7B-fp16](https://huggingface.co/TheBloke/Lla... | {"library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "TheBloke/Llama-2-7B-fp16", "model-index": [{"name": "Saiga_timelist_task100steps", "results": []}]} | marcus2000/Saiga_timelist_task100steps | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:TheBloke/Llama-2-7B-fp16",
"region:us"
] | null | 2024-04-23T08:26:40+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-TheBloke/Llama-2-7B-fp16 #region-us
| Saiga\_timelist\_task100steps
=============================
This model is a fine-tuned version of TheBloke/Llama-2-7B-fp16 on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 1.7978
Model description
-----------------
More information needed
Intended uses & limitations
------... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-06\n* train\\_batch\\_size: 2\n* eval\\_batch\\_size: 8\n* seed: 42\n* gradient\\_accumulation\\_steps: 5\n* total\\_train\\_batch\\_size: 10\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1... | [
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feature-extraction | transformers |
# megatron.bert-large.bpe-64k-no_pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done ... | {"language": ["sv"]} | KBLab/megatron.bert-large.bpe-64k-no_pretok.25k-steps | null | [
"transformers",
"safetensors",
"megatron-bert",
"feature-extraction",
"sv",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:26:56+00:00 | [] | [
"sv"
] | TAGS
#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us
|
# URL-64k-no_pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 25k training ste... | [
"# URL-64k-no_pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.\n\nTraining was done for 25k tr... | [
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487,
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"TAGS\n#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us \n# URL-64k-no_pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of web... |
text-generation | transformers |
# Meta-Llama-3-8B-Instruct-GGUF
- This is GGUF quantized version of [lcw99/llama-3-8b-it-ko-chang](https://huggingface.co/lcw99/llama-3-8b-it-ko-chang) created using llama.cpp
### Model Description
Korean instruction tunning of meta-llama/Meta-Llama-3-8B-Instruct
#### Chat template
**system:** system message... ... | {"language": ["ko"], "license": "other", "library_name": "transformers", "tags": ["facebook", "meta", "pytorch", "llama", "llama-3"], "pipeline_tag": "text-generation", "base_model": "lcw99/llama-3-8b-it-ko-chang"} | existmaster/llama-3-8b-it-ko-chang-GGUF | null | [
"transformers",
"gguf",
"facebook",
"meta",
"pytorch",
"llama",
"llama-3",
"text-generation",
"ko",
"base_model:lcw99/llama-3-8b-it-ko-chang",
"license:other",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:27:22+00:00 | [] | [
"ko"
] | TAGS
#transformers #gguf #facebook #meta #pytorch #llama #llama-3 #text-generation #ko #base_model-lcw99/llama-3-8b-it-ko-chang #license-other #endpoints_compatible #region-us
|
# Meta-Llama-3-8B-Instruct-GGUF
- This is GGUF quantized version of lcw99/llama-3-8b-it-ko-chang created using URL
### Model Description
Korean instruction tunning of meta-llama/Meta-Llama-3-8B-Instruct
#### Chat template
system: system message...
B: user message...
A: assistant message...
| [
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"### Model Description\n\nKorean instruction tunning of meta-llama/Meta-Llama-3-8B-Instruct",
"#### Chat template\n\nsystem: system message... \nB: user message... \nA: assistant message...... | [
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"# Meta-Llama-3-8B-Instruct-GGUF\n\n- This is GGUF quantized version of lcw99/llama-3-8b-it-ko-chang created using URL",
"### Mod... | [
66,
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"TAGS\n#transformers #gguf #facebook #meta #pytorch #llama #llama-3 #text-generation #ko #base_model-lcw99/llama-3-8b-it-ko-chang #license-other #endpoints_compatible #region-us \n# Meta-Llama-3-8B-Instruct-GGUF\n\n- This is GGUF quantized version of lcw99/llama-3-8b-it-ko-chang created using URL### Model Descripti... |
question-answering | transformers |
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# krishrveera/my_qa_model
This model is a fine-tuned version of [deepset/roberta-base-squad2](https://huggingface.co/deepset/roberta-bas... | {"license": "cc-by-4.0", "tags": ["generated_from_keras_callback"], "base_model": "deepset/roberta-base-squad2", "model-index": [{"name": "krishrveera/my_qa_model", "results": []}]} | krishrveera/my_qa_model | null | [
"transformers",
"tf",
"roberta",
"question-answering",
"generated_from_keras_callback",
"base_model:deepset/roberta-base-squad2",
"license:cc-by-4.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:27:28+00:00 | [] | [] | TAGS
#transformers #tf #roberta #question-answering #generated_from_keras_callback #base_model-deepset/roberta-base-squad2 #license-cc-by-4.0 #endpoints_compatible #region-us
| krishrveera/my\_qa\_model
=========================
This model is a fine-tuned version of deepset/roberta-base-squad2 on an unknown dataset.
It achieves the following results on the evaluation set:
* Train Loss: 2.0494
* Validation Loss: 2.0947
* Epoch: 2
Model description
-----------------
More information nee... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* optimizer: {'name': 'Adam', 'weight\\_decay': None, 'clipnorm': None, 'global\\_clipnorm': None, 'clipvalue': None, 'use\\_ema': False, 'ema\\_momentum': 0.99, 'ema\\_overwrite\\_frequency': None, 'jit\\_compile': Tru... | [
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feature-extraction | transformers |
# megatron.bert-large.spe-bpe-32k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done... | {"language": ["sv"]} | KBLab/megatron.bert-large.spe-bpe-32k-pretok.25k-steps | null | [
"transformers",
"safetensors",
"megatron-bert",
"feature-extraction",
"sv",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:28:25+00:00 | [] | [
"sv"
] | TAGS
#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us
|
# URL-bpe-32k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 25k training st... | [
"# URL-bpe-32k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.\n\nTraining was done for 25k t... | [
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"# URL-bpe-32k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly... | [
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"TAGS\n#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us \n# URL-bpe-32k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of we... |
text-generation | null | Further trained on custom dataset with this system prompt:
```text
<|im_start|>system
You are JOSIE, my private and superinteligent AI Assistant.<|im_end|>
<|im_start|>user
{{ .Prompt }}<|im_end|>
<|im_start|>assistant
{{ .Response }}<|im_end|>
``` | {"language": ["en", "de"], "license": "apache-2.0", "pipeline_tag": "text-generation"} | Isaak-Carter/J.O.S.I.E.3-Beta12-7B-slerp-gguf | null | [
"gguf",
"text-generation",
"en",
"de",
"license:apache-2.0",
"region:us"
] | null | 2024-04-23T08:28:51+00:00 | [] | [
"en",
"de"
] | TAGS
#gguf #text-generation #en #de #license-apache-2.0 #region-us
| Further trained on custom dataset with this system prompt:
| [] | [
"TAGS\n#gguf #text-generation #en #de #license-apache-2.0 #region-us \n"
] | [
25
] | [
"TAGS\n#gguf #text-generation #en #de #license-apache-2.0 #region-us \n"
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feature-extraction | transformers |
# megatron.bert-large.unigram-32k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done... | {"language": ["sv"]} | KBLab/megatron.bert-large.unigram-32k-pretok.25k-steps | null | [
"transformers",
"safetensors",
"megatron-bert",
"feature-extraction",
"sv",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:29:42+00:00 | [] | [
"sv"
] | TAGS
#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us
|
# URL-large.unigram-32k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 25k t... | [
"# URL-large.unigram-32k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.\n\nTraining was done... | [
"TAGS\n#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us \n",
"# URL-large.unigram-32k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consist... | [
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"TAGS\n#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us \n# URL-large.unigram-32k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mo... |
text-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# modelofine
This model is a fine-tuned version of [projecte-aina/roberta-base-ca-v2-cased-te](https://huggingface.co/projecte-ain... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "projecte-aina/roberta-base-ca-v2-cased-te", "model-index": [{"name": "modelofine", "results": []}]} | adriansanz/modelofine | null | [
"transformers",
"safetensors",
"roberta",
"text-classification",
"generated_from_trainer",
"base_model:projecte-aina/roberta-base-ca-v2-cased-te",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:29:42+00:00 | [] | [] | TAGS
#transformers #safetensors #roberta #text-classification #generated_from_trainer #base_model-projecte-aina/roberta-base-ca-v2-cased-te #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us
|
# modelofine
This model is a fine-tuned version of projecte-aina/roberta-base-ca-v2-cased-te on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8036
- Accuracy: 0.0672
## Model description
More information needed
## Intended uses & limitations
More information needed
## Tra... | [
"# modelofine\n\nThis model is a fine-tuned version of projecte-aina/roberta-base-ca-v2-cased-te on the None dataset.\nIt achieves the following results on the evaluation set:\n- Loss: 2.8036\n- Accuracy: 0.0672",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore informa... | [
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text-generation | transformers | design2code-hf from https://huggingface.co/SALT-NLP/Design2Code-18B-v0 | {"license": "mit"} | yeelou/design2code-hf | null | [
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"region:us"
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#transformers #safetensors #text-generation #custom_code #license-mit #autotrain_compatible #region-us
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null | null | pics of masjid | {} | fani4415/jh | null | [
"region:us"
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#region-us
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feature-extraction | transformers |
# megatron.bert-large.unigram-64k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done... | {"language": ["sv"]} | KBLab/megatron.bert-large.unigram-64k-pretok.25k-steps | null | [
"transformers",
"safetensors",
"megatron-bert",
"feature-extraction",
"sv",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:31:02+00:00 | [] | [
"sv"
] | TAGS
#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us
|
# URL-large.unigram-64k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 25k t... | [
"# URL-large.unigram-64k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.\n\nTraining was done... | [
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text-generation | transformers |
## About Quantization
我们使用modelscope [swift](https://github.com/modelscope/swift/)仓库进行GPTQ量化. 量化文档可以查看[这里](https://github.com/modelscope/swift/blob/main/docs/source/LLM/LLM%E9%87%8F%E5%8C%96%E6%96%87%E6%A1%A3.md). 量化命令如下:
We use the modelscope [swift](https://github.com/modelscope/swift/) repository to perform GPTQ q... | {"language": ["en"], "license": "other", "tags": ["awq", "int8", "llama3", "facebook", "meta", "pytorch", "llama", "llama-3"], "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE", "extra_gated_prompt": "### META LLAMA 3 COMMUNITY LICENSE AGREEMENT\nMeta Llama 3 Version Release Date: A... | study-hjt/Meta-Llama-3-8B-Instruct-GPTQ-Int8 | null | [
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"conversational",
"en",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"8-bit",
"region:us"
] | null | 2024-04-23T08:32:00+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #llama #text-generation #awq #int8 #llama3 #facebook #meta #pytorch #llama-3 #conversational #en #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #8-bit #region-us
| About Quantization
------------------
我们使用modelscope swift仓库进行GPTQ量化. 量化文档可以查看这里. 量化命令如下:
We use the modelscope swift repository to perform GPTQ quantization. Quantization documentation can be found here. The quantization command is as follows:
Inference:
SFT:
Model Details
-------------
Meta developed and ... | [
"### Use with transformers\n\n\nSee the snippet below for usage with Transformers:",
"### Use with 'llama3'\n\n\nPlease, follow the instructions in the repository\n\n\nTo download Original checkpoints, see the example command below leveraging 'huggingface-cli':\n\n\nFor Hugging Face support, we recommend using tr... | [
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feature-extraction | transformers |
# megatron.bert-large.wordpiece-32k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was do... | {"language": ["sv"]} | KBLab/megatron.bert-large.wordpiece-32k-pretok.25k-steps | null | [
"transformers",
"safetensors",
"megatron-bert",
"feature-extraction",
"sv",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:32:25+00:00 | [] | [
"sv"
] | TAGS
#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us
|
# URL-large.wordpiece-32k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 25k... | [
"# URL-large.wordpiece-32k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.\n\nTraining was do... | [
"TAGS\n#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us \n",
"# URL-large.wordpiece-32k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consi... | [
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"TAGS\n#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us \n# URL-large.wordpiece-32k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting ... |
object-detection | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# detr-resnet-50_finetuned_cppe5
This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/d... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "facebook/detr-resnet-50", "model-index": [{"name": "detr-resnet-50_finetuned_cppe5", "results": []}]} | SkowKyubu/detr-resnet-50_finetuned_cppe5 | null | [
"transformers",
"tensorboard",
"safetensors",
"detr",
"object-detection",
"generated_from_trainer",
"base_model:facebook/detr-resnet-50",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:33:04+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #detr #object-detection #generated_from_trainer #base_model-facebook/detr-resnet-50 #license-apache-2.0 #endpoints_compatible #region-us
|
# detr-resnet-50_finetuned_cppe5
This model is a fine-tuned version of facebook/detr-resnet-50 on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training... | [
"# detr-resnet-50_finetuned_cppe5\n\nThis model is a fine-tuned version of facebook/detr-resnet-50 on an unknown dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Traini... | [
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"# detr-resnet-50_finetuned_cppe5\n\nThis model is a fine-tuned version of facebook/detr-resnet-50 on an unknown dataset.",
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text-generation | transformers |
## Model Details
This is meta-llama/Meta-Llama-3-8B quantized and serialized with AutoAWQ in 4-bit.
Details here:
[Fine-tune Llama 3 on Your Computer](https://kaitchup.substack.com/p/fine-tune-llama-3-on-your-computer)
- **Developed by:** [The Kaitchup](https://kaitchup.substack.com/)
- **Language(s) (NLP):** E... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["autoawq"]} | kaitchup/Llama-3-8b-awq-4bit | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
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"en",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"4-bit",
"region:us"
] | null | 2024-04-23T08:33:46+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #llama #text-generation #autoawq #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
|
## Model Details
This is meta-llama/Meta-Llama-3-8B quantized and serialized with AutoAWQ in 4-bit.
Details here:
Fine-tune Llama 3 on Your Computer
- Developed by: The Kaitchup
- Language(s) (NLP): English
- License: Apache 2.0 license ; You must also accept the Llama 3 license | [
"## Model Details\n\nThis is meta-llama/Meta-Llama-3-8B quantized and serialized with AutoAWQ in 4-bit. \n\nDetails here:\n\nFine-tune Llama 3 on Your Computer\n\n\n- Developed by: The Kaitchup\n- Language(s) (NLP): English\n- License: Apache 2.0 license ; You must also accept the Llama 3 license"
] | [
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"TAGS\n#transformers #safetensors #llama #text-generation #autoawq #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us \n## Model Details\n\nThis is meta-llama/Meta-Llama-3-8B quantized and serialized with AutoAWQ in 4-bit. \n\nDetails here:\n\nFine-tune ... |
feature-extraction | transformers |
# megatron.bert-large.wordpiece-64k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was do... | {"language": ["sv"]} | KBLab/megatron.bert-large.wordpiece-64k-pretok.25k-steps | null | [
"transformers",
"safetensors",
"megatron-bert",
"feature-extraction",
"sv",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:33:48+00:00 | [] | [
"sv"
] | TAGS
#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us
|
# URL-large.wordpiece-64k-pretok.25k-steps
This BERT model was trained using the NeMo library.
The size of the model is a regular bert-large.
The model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.
Training was done for 25k... | [
"# URL-large.wordpiece-64k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting mostly of web-data and Swedish newspaper text curated by the National Library of Sweden.\n\nTraining was do... | [
"TAGS\n#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us \n",
"# URL-large.wordpiece-64k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consi... | [
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"TAGS\n#transformers #safetensors #megatron-bert #feature-extraction #sv #endpoints_compatible #region-us \n# URL-large.wordpiece-64k-pretok.25k-steps\n\nThis BERT model was trained using the NeMo library.\nThe size of the model is a regular bert-large.\nThe model was trained on more than 245GB of data, consisting ... |
text-generation | transformers |
# hus960/openbuddy-qwen1.5-14b-v21.1-32k-Q4_K_M-GGUF
This model was converted to GGUF format from [`OpenBuddy/openbuddy-qwen1.5-14b-v21.1-32k`](https://huggingface.co/OpenBuddy/openbuddy-qwen1.5-14b-v21.1-32k) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
... | {"language": ["zh", "en", "fr", "de", "ja", "ko", "it", "ru", "fi"], "license": "other", "library_name": "transformers", "tags": ["llama-cpp", "gguf-my-repo"], "license_name": "tongyi-qianwen-license-agreement", "license_link": "https://huggingface.co/Qwen/Qwen1.5-14B/blob/39b74a78357df4d2296e838d87565967d663a67a/LICEN... | hus960/openbuddy-qwen1.5-14b-v21.1-32k-Q4_K_M-GGUF | null | [
"transformers",
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"zh",
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"fr",
"de",
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"ko",
"it",
"ru",
"fi",
"license:other",
"region:us"
] | null | 2024-04-23T08:36:22+00:00 | [] | [
"zh",
"en",
"fr",
"de",
"ja",
"ko",
"it",
"ru",
"fi"
] | TAGS
#transformers #gguf #llama-cpp #gguf-my-repo #text-generation #zh #en #fr #de #ja #ko #it #ru #fi #license-other #region-us
|
# hus960/openbuddy-qwen1.5-14b-v21.1-32k-Q4_K_M-GGUF
This model was converted to GGUF format from 'OpenBuddy/openbuddy-qwen1.5-14b-v21.1-32k' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or... | [
"# hus960/openbuddy-qwen1.5-14b-v21.1-32k-Q4_K_M-GGUF\nThis model was converted to GGUF format from 'OpenBuddy/openbuddy-qwen1.5-14b-v21.1-32k' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
"## Use with URL\n\nInstall URL through brew.\n\n\nInvoke t... | [
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"TAGS\n#transformers #gguf #llama-cpp #gguf-my-repo #text-generation #zh #en #fr #de #ja #ko #it #ru #fi #license-other #region-us \n# hus960/openbuddy-qwen1.5-14b-v21.1-32k-Q4_K_M-GGUF\nThis model was converted to GGUF format from 'OpenBuddy/openbuddy-qwen1.5-14b-v21.1-32k' using URL via the URL's GGUF-my-repo spa... |
object-detection | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# detr
This model is a fine-tuned version of [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) on an unkno... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "facebook/detr-resnet-50", "model-index": [{"name": "detr", "results": []}]} | Maksim-Ploter/detr | null | [
"transformers",
"tensorboard",
"safetensors",
"detr",
"object-detection",
"generated_from_trainer",
"base_model:facebook/detr-resnet-50",
"license:apache-2.0",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T08:38:16+00:00 | [] | [] | TAGS
#transformers #tensorboard #safetensors #detr #object-detection #generated_from_trainer #base_model-facebook/detr-resnet-50 #license-apache-2.0 #endpoints_compatible #region-us
| detr
====
This model is a fine-tuned version of facebook/detr-resnet-50 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 5.7762
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information needed
... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.001\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 1\n* mixed\\_preci... | [
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"TAGS\n#transformers #tensorboard #safetensors #detr #object-detection #generated_from_trainer #base_model-facebook/detr-resnet-50 #license-apache-2.0 #endpoints_compatible #region-us \n### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 0.001\n* train\... |
text-generation | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# I-Heart_sft_1.0
This model was trained from scratch on the generator dataset.
It achieves the following results on the evaluatio... | {"tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "model-index": [{"name": "I-Heart_sft_1.0", "results": []}]} | Pain-Killer/I-Heart_sft_1.0 | null | [
"transformers",
"tensorboard",
"safetensors",
"mistral",
"text-generation",
"trl",
"sft",
"generated_from_trainer",
"conversational",
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"autotrain_compatible",
"endpoints_compatible",
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"region:us"
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#transformers #tensorboard #safetensors #mistral #text-generation #trl #sft #generated_from_trainer #conversational #dataset-generator #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
| I-Heart\_sft\_1.0
=================
This model was trained from scratch on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 1.0549
Model description
-----------------
More information needed
Intended uses & limitations
---------------------------
More information neede... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Saiga_timelist_task10steps
This model is a fine-tuned version of [TheBloke/Llama-2-7B-fp16](https://huggingface.co/TheBloke/Llam... | {"library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "TheBloke/Llama-2-7B-fp16", "model-index": [{"name": "Saiga_timelist_task10steps", "results": []}]} | marcus2000/Saiga_timelist_task10steps | null | [
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#peft #safetensors #generated_from_trainer #base_model-TheBloke/Llama-2-7B-fp16 #region-us
| Saiga\_timelist\_task10steps
============================
This model is a fine-tuned version of TheBloke/Llama-2-7B-fp16 on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 2.1174
Model description
-----------------
More information needed
Intended uses & limitations
------... | [
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reinforcement-learning | stable-baselines3 |
# **PPO** Agent playing **LunarLander-v2**
This is a trained model of a **PPO** agent playing **LunarLander-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
## Usage (with Stable-baselines3)
TODO: Add your code
```python
from stable_baselines3 import ...
from huggingface_sb3 ... | {"library_name": "stable-baselines3", "tags": ["LunarLander-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "PPO", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "LunarLander-v2", "type": "LunarL... | JoeBater/ppo-LunarLander-v2 | null | [
"stable-baselines3",
"LunarLander-v2",
"deep-reinforcement-learning",
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"model-index",
"region:us"
] | null | 2024-04-23T08:39:47+00:00 | [] | [] | TAGS
#stable-baselines3 #LunarLander-v2 #deep-reinforcement-learning #reinforcement-learning #model-index #region-us
|
# PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2
using the stable-baselines3 library.
## Usage (with Stable-baselines3)
TODO: Add your code
| [
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] |
text-classification | setfit |
# SetFit with BAAI/bge-small-en-v1.5
This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) as the Sentence Transformer embedding model. A [LogisticRegression](https://scik... | {"library_name": "setfit", "tags": ["setfit", "sentence-transformers", "text-classification", "generated_from_setfit_trainer"], "metrics": ["accuracy"], "base_model": "BAAI/bge-small-en-v1.5", "widget": [{"text": "Can you tell me about any on9uin9 promotions uk discounts on organic pk0doce?"}, {"text": "I bought 80meth... | wikd/setfit-bge-small-v1.5-sst2-nlapug_rand_aug | null | [
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| SetFit with BAAI/bge-small-en-v1.5
==================================
This is a SetFit model that can be used for Text Classification. This SetFit model uses BAAI/bge-small-en-v1.5 as the Sentence Transformer embedding model. A LogisticRegression instance is used for classification.
The model has been trained using... | [
"### Model Description\n\n\n* Model Type: SetFit\n* Sentence Transformer body: BAAI/bge-small-en-v1.5\n* Classification head: a LogisticRegression instance\n* Maximum Sequence Length: 512 tokens\n* Number of Classes: 5 classes",
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Llama2-70b-Instruct-finetuned
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-70B-Instruct](https://huggingface.c... | {"license": "other", "library_name": "peft", "tags": ["trl", "sft", "generated_from_trainer"], "datasets": ["generator"], "base_model": "meta-llama/Meta-Llama-3-70B-Instruct", "model-index": [{"name": "Llama2-70b-Instruct-finetuned", "results": []}]} | Utshav/Llama3-70b-Instruct-extractor-adaptor | null | [
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"base_model:meta-llama/Meta-Llama-3-70B-Instruct",
"license:other",
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#peft #safetensors #trl #sft #generated_from_trainer #dataset-generator #base_model-meta-llama/Meta-Llama-3-70B-Instruct #license-other #region-us
| Llama2-70b-Instruct-finetuned
=============================
This model is a fine-tuned version of meta-llama/Meta-Llama-3-70B-Instruct on the generator dataset.
It achieves the following results on the evaluation set:
* Loss: 0.6518
Model description
-----------------
More information needed
Intended uses & l... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2.5e-05\n* train\\_batch\\_size: 1\n* eval\\_batch\\_size: 8\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* lr\\_scheduler\\_warmup\\_steps... | [
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text-generation | transformers | # Llama-3-6B-Instruct-pruned
*Experimental*
Using [PruneMe](https://github.com/arcee-ai/PruneMe) to find minimal average distance. Thank you for awesome toolkit @arcee-ai !
<img src="./distance.png" alt="distance" width="390"/>
*It shows pruning the 22-30 layer is the best option, but I'm worried about drasitical chan... | {"library_name": "transformers", "tags": ["mergekit", "merge"], "base_model": ["meta-llama/Meta-Llama-3-8B-Instruct"]} | kuotient/Llama-3-6B-Instruct-pruned | null | [
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| # Llama-3-6B-Instruct-pruned
*Experimental*
Using PruneMe to find minimal average distance. Thank you for awesome toolkit @arcee-ai !
<img src="./URL" alt="distance" width="390"/>
*It shows pruning the 22-30 layer is the best option, but I'm worried about drasitical change between 22 to 23.*
### Disclaimer
I haven't ... | [
"# Llama-3-6B-Instruct-pruned\n*Experimental*\n\nUsing PruneMe to find minimal average distance. Thank you for awesome toolkit @arcee-ai !\n<img src=\"./URL\" alt=\"distance\" width=\"390\"/>\n*It shows pruning the 22-30 layer is the best option, but I'm worried about drasitical change between 22 to 23.*",
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null | transformers |
# RachidAR/llama3-Mirage-Walker-8b-v0.2-slerp-Q6_K-GGUF
This model was converted to GGUF format from [`taozi555/llama3-Mirage-Walker-8b-v0.2-slerp`](https://huggingface.co/taozi555/llama3-Mirage-Walker-8b-v0.2-slerp) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) ... | {"library_name": "transformers", "tags": ["mergekit", "merge", "llama-cpp", "gguf-my-repo"], "base_model": ["meta-llama/Meta-Llama-3-8B-Instruct"]} | RachidAR/llama3-Mirage-Walker-8b-v0.2-slerp-Q6_K-GGUF | null | [
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#transformers #gguf #mergekit #merge #llama-cpp #gguf-my-repo #base_model-meta-llama/Meta-Llama-3-8B-Instruct #endpoints_compatible #region-us
|
# RachidAR/llama3-Mirage-Walker-8b-v0.2-slerp-Q6_K-GGUF
This model was converted to GGUF format from 'taozi555/llama3-Mirage-Walker-8b-v0.2-slerp' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL serv... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | guptasaurabh78/ph2-sau-samsum-ft-2 | null | [
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|
# Model Card for Model ID
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | OwOOwO/dumbo-llamalfg5 | null | [
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null | transformers |
# LeroyDyer/Mixtral_AI_CyberUltron-Q4_K_M-GGUF
This model was converted to GGUF format from [`LeroyDyer/Mixtral_AI_CyberUltron`](https://huggingface.co/LeroyDyer/Mixtral_AI_CyberUltron) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original m... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl", "code", "medical ", "farmer", "doctor", "Mega-Series", "Cyber-Series", "Role-Play", "Self-Rag", "ThinkingBot", "milestone", "mega-series", "SpydazWebAI", "llam... | LeroyDyer/Mixtral_AI_CyberUltron-Q4_K_M-GGUF | null | [
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# LeroyDyer/Mixtral_AI_CyberUltron-Q4_K_M-GGUF
This model was converted to GGUF format from 'LeroyDyer/Mixtral_AI_CyberUltron' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.
CLI:... | [
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"## Use with URL\n\nInstall URL through brew.\n\n\nInvoke the URL server o... | [
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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# Model Card for Model ID
## Model Details
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
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<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Shared by [optional]:** [More Information Needed]
- **Model type:** [More Info... | {"library_name": "peft", "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0"} | bmehrba/TinyLlama-1.1B-Chat-v1.0-fine-tuned_Aleatoric_tiny_0.0_Seed101 | null | [
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### Model Description
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token-classification | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | rizkyfoxcale/xlm-roberta-large-ner-iob-ja | null | [
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### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | peft |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
- **Developed by:** [More Information Needed]
- **Funded by [optional]:** [More Information Needed]
- **Shared by [optional]:** ... | {"library_name": "peft", "base_model": "Trelis/Llama-2-7b-chat-hf-sharded-bf16"} | SinkableVirus/LlamaStories_96Epoch | null | [
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## Model Details
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token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# trained_baseline
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/di... | {"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "distilbert/distilbert-base-uncased", "model-index": [{"name": "trained_baseline", "results": []}]} | annamariagnat/trained_baseline | null | [
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| trained\_baseline
=================
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset.
It achieves the following results on the evaluation set:
* Loss: 0.0834
* Precision: 0.7505
* Recall: 0.7625
* F1: 0.7565
* Accuracy: 0.9782
Model description
-----------------
More ... | [
"### Training hyperparameters\n\n\nThe following hyperparameters were used during training:\n\n\n* learning\\_rate: 2e-05\n* train\\_batch\\_size: 16\n* eval\\_batch\\_size: 16\n* seed: 42\n* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08\n* lr\\_scheduler\\_type: linear\n* num\\_epochs: 3",
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null | transformers |
# RachidAR/Llama-3-8B-Instruct-Physics-5k-Scar-Q6_K-GGUF
This model was converted to GGUF format from [`nmdr/Llama-3-8B-Instruct-Physics-5k-Scar`](https://huggingface.co/nmdr/Llama-3-8B-Instruct-Physics-5k-Scar) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space... | {"library_name": "transformers", "tags": ["llama-cpp", "gguf-my-repo"]} | RachidAR/Llama-3-8B-Instruct-Physics-5k-Scar-Q6_K-GGUF | null | [
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|
# RachidAR/Llama-3-8B-Instruct-Physics-5k-Scar-Q6_K-GGUF
This model was converted to GGUF format from 'nmdr/Llama-3-8B-Instruct-Physics-5k-Scar' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server... | [
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null | transformers |
# LeroyDyer/Mixtral_AI_Ultron-Q4_K_M-GGUF
This model was converted to GGUF format from [`LeroyDyer/Mixtral_AI_Ultron`](https://huggingface.co/LeroyDyer/Mixtral_AI_Ultron) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](http... | {"language": ["en"], "license": "apache-2.0", "library_name": "transformers", "tags": ["text-generation-inference", "transformers", "unsloth", "mistral", "trl", "code", "medical ", "farmer", "doctor", "Mega-Series", "Cyber-Series", "Role-Play", "Self-Rag", "ThinkingBot", "milestone", "mega-series", "SpydazWebAI", "llam... | LeroyDyer/Mixtral_AI_Ultron-Q4_K_M-GGUF | null | [
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#transformers #gguf #text-generation-inference #unsloth #mistral #trl #code #medical #farmer #doctor #Mega-Series #Cyber-Series #Role-Play #Self-Rag #ThinkingBot #milestone #mega-series #SpydazWebAI #llama-cpp #gguf-my-repo #en #dataset-gretelai/synthetic_text_to_sql #dataset-HuggingFaceTB/cosmopedia #dataset-tek... |
# LeroyDyer/Mixtral_AI_Ultron-Q4_K_M-GGUF
This model was converted to GGUF format from 'LeroyDyer/Mixtral_AI_Ultron' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.
CLI:
Server... | [
"# LeroyDyer/Mixtral_AI_Ultron-Q4_K_M-GGUF\nThis model was converted to GGUF format from 'LeroyDyer/Mixtral_AI_Ultron' using URL via the URL's GGUF-my-repo space.\nRefer to the original model card for more details on the model.",
"## Use with URL\n\nInstall URL through brew.\n\n\nInvoke the URL server or the CLI.... | [
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null | transformers |
# RachidAR/ablation-model-fineweb-v1-Q6_K-GGUF
This model was converted to GGUF format from [`HuggingFaceFW/ablation-model-fineweb-v1`](https://huggingface.co/HuggingFaceFW/ablation-model-fineweb-v1) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to t... | {"library_name": "transformers", "tags": ["llama-cpp", "gguf-my-repo"]} | RachidAR/ablation-model-fineweb-v1-Q6_K-GGUF | null | [
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#transformers #gguf #llama-cpp #gguf-my-repo #endpoints_compatible #region-us
|
# RachidAR/ablation-model-fineweb-v1-Q6_K-GGUF
This model was converted to GGUF format from 'HuggingFaceFW/ablation-model-fineweb-v1' using URL via the URL's GGUF-my-repo space.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI... | [
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null | peft | ## Training procedure
The following `bitsandbytes` quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_... | {"library_name": "peft"} | Hardik1234/llama-finetune-reactjs | null | [
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"region:us"
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#peft #pytorch #has_space #region-us
| ## Training procedure
The following 'bitsandbytes' quantization config was used during training:
- quant_method: bitsandbytes
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- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
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- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_... | [
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null | null | # NorskGPT-Llama-3-8b-v0.1
This model is a Norwegian variant of
Meta-Llama-3-8B, fine-tuned on a carefully selected mix of Norwegian instruction pairs. The model is tuned to understand and generate text in Norwegain.
## Intended Use
This model is free to use for personal and research use. However a commercial lic... | {"language": [false], "license": "cc-by-nc-sa-4.0", "tags": ["llama", "NorskGPT", "instruct", "finetune"], "base_model": "bineric/NorskGPT-Llama3-8b"} | bineric/NorskGPT-Llama3-8b-GGUF | null | [
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| NorskGPT-Llama-3-8b-v0.1
========================
This model is a Norwegian variant of
Meta-Llama-3-8B, fine-tuned on a carefully selected mix of Norwegian instruction pairs. The model is tuned to understand and generate text in Norwegain.
Intended Use
------------
This model is free to use for personal and resea... | [
"### About GGUF\n\n\nHere is an incomplete list of clients and libraries that are known to support GGUF:\n\n\n* URL. The source project for GGUF. Offers a CLI and a server option.\n* text-generation-webui, the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration.\n* KoboldC... | [
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text-generation | fastai |
# BasedBots/cosmo-1b-Q4_K_M-GGUF
This model was converted to GGUF format from [`HuggingFaceTB/cosmo-1b`](https://huggingface.co/HuggingFaceTB/cosmo-1b) using llama.cpp.
Refer to the [original model card](https://huggingface.co/HuggingFaceTB/cosmo-1b) for more details on the model.
## Use with llama.cpp
Install llama.... | {"language": ["en"], "license": "apache-2.0", "library_name": "fastai", "tags": ["llama-cpp", "gguf-my-repo"], "datasets": ["HuggingFaceTB/cosmopedia"], "inference": {"parameters": {"temperature": 0.6, "top_p": 0.95, "top_k": 50, "repetition_penalty": 1.2}}, "widget": [{"text": "Photosynthesis is", "example_title": "Te... | BasedBots/cosmo-1b-Q4_K_M-GGUF | null | [
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"en"
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#fastai #gguf #llama-cpp #gguf-my-repo #text-generation #en #dataset-HuggingFaceTB/cosmopedia #license-apache-2.0 #region-us
|
# BasedBots/cosmo-1b-Q4_K_M-GGUF
This model was converted to GGUF format from 'HuggingFaceTB/cosmo-1b' using URL.
Refer to the original model card for more details on the model.
## Use with URL
Install URL through brew.
Invoke the URL server or the CLI.
CLI:
Server:
Note: You can also use this checkpoint dir... | [
"# BasedBots/cosmo-1b-Q4_K_M-GGUF\nThis model was converted to GGUF format from 'HuggingFaceTB/cosmo-1b' using URL.\nRefer to the original model card for more details on the model.",
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token-classification | transformers |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-base-finetuned-panx-de
This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-b... | {"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1"], "base_model": "xlm-roberta-base", "model-index": [{"name": "xlm-roberta-base-finetuned-panx-de", "results": []}]} | jung2002/xlm-roberta-base-finetuned-panx-de | null | [
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| xlm-roberta-base-finetuned-panx-de
==================================
This model is a fine-tuned version of xlm-roberta-base on an unknown dataset.
It achieves the following results on the evaluation set:
* Loss: 0.1363
* F1: 0.8658
Model description
-----------------
More information needed
Intended uses & l... | [
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fill-mask | transformers |
# Model Card for Astro-HEP-BERT
**Astro-HEP-BERT** is a bidirectional transformer designed primarily to generate contextualized word embeddings for analyzing epistemic change in astrophysics and high-energy physics (see <a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.3030/101044932" >NEPI resear... | {"language": ["en"], "license": "apache-2.0", "tags": ["physics", "astrophysics", "high-energy physics (HEP)", "history of science", "philosophy of science", "sociology of science", "epistemic change", "arXiv"], "datasets": ["wikipedia", "bookcorpus"], "pipeline_tag": "fill-mask", "widget": [{"text": "The Standard Mode... | arnosimons/astro-hep-bert | null | [
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|
# Model Card for Astro-HEP-BERT
Astro-HEP-BERT is a bidirectional transformer designed primarily to generate contextualized word embeddings for analyzing epistemic change in astrophysics and high-energy physics (see <a target="_blank" rel="noopener noreferrer" href="URL >NEPI research project</a>). Built upon Google'... | [
"# Model Card for Astro-HEP-BERT\n\nAstro-HEP-BERT is a bidirectional transformer designed primarily to generate contextualized word embeddings for analyzing epistemic change in astrophysics and high-energy physics (see <a target=\"_blank\" rel=\"noopener noreferrer\" href=\"URL >NEPI research project</a>). Built u... | [
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"license": "apache-2.0", "library_name": "transformers"} | T3Q-LLM/T3Q-LLM-sft1.1-dpo1.0 | null | [
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|
# Model Card for Model ID
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This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | Utshav/LLama3-70b-Instruct-finetuned-extractions | null | [
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text-generation | null |
# m0javad/Meta-Llama-3-8B-Q8_0-GGUF
This model was converted to GGUF format from [`meta-llama/Meta-Llama-3-8B`](https://huggingface.co/meta-llama/Meta-Llama-3-8B)
Refer to the [original model card](https://huggingface.co/meta-llama/Meta-Llama-3-8B) for more details on the model.
| {"language": ["en"], "license": "other", "tags": ["facebook", "meta", "pytorch", "llama", "llama-3", "llama-cpp", "gguf-my-repo"], "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE", "extra_gated_prompt": "### META LLAMA 3 COMMUNITY LICENSE AGREEMENT\nMeta Llama 3 Version Release Dat... | m0javad/Meta-Llama-3-8B-Q8_0-GGUF | null | [
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"license:other",
"region:us"
] | null | 2024-04-23T09:05:26+00:00 | [] | [
"en"
] | TAGS
#gguf #facebook #meta #pytorch #llama #llama-3 #llama-cpp #gguf-my-repo #text-generation #en #license-other #region-us
|
# m0javad/Meta-Llama-3-8B-Q8_0-GGUF
This model was converted to GGUF format from 'meta-llama/Meta-Llama-3-8B'
Refer to the original model card for more details on the model.
| [
"# m0javad/Meta-Llama-3-8B-Q8_0-GGUF\nThis model was converted to GGUF format from 'meta-llama/Meta-Llama-3-8B' \nRefer to the original model card for more details on the model."
] | [
"TAGS\n#gguf #facebook #meta #pytorch #llama #llama-3 #llama-cpp #gguf-my-repo #text-generation #en #license-other #region-us \n",
"# m0javad/Meta-Llama-3-8B-Q8_0-GGUF\nThis model was converted to GGUF format from 'meta-llama/Meta-Llama-3-8B' \nRefer to the original model card for more details on the model."
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] |
null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | twodigit/meta-llama-Meta-Llama-3-8B-Instruct-kocomp_900_llama3_8b-dpo-lora-lr1e-5-e1-b4 | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T09:06:56+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
"# Model Card for Model ID",
"## Model Details",
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"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Devel... | [
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null | peft |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# HSE_PRAVO_complexity_classifier3
This model is a fine-tuned version of [ai-forever/ruBert-base](https://huggingface.co/ai-foreve... | {"license": "apache-2.0", "library_name": "peft", "tags": ["generated_from_trainer"], "base_model": "ai-forever/ruBert-base", "model-index": [{"name": "HSE_PRAVO_complexity_classifier3", "results": []}]} | marcus2000/HSE_PRAVO_complexity_classifier3 | null | [
"peft",
"safetensors",
"generated_from_trainer",
"base_model:ai-forever/ruBert-base",
"license:apache-2.0",
"region:us"
] | null | 2024-04-23T09:07:04+00:00 | [] | [] | TAGS
#peft #safetensors #generated_from_trainer #base_model-ai-forever/ruBert-base #license-apache-2.0 #region-us
|
# HSE_PRAVO_complexity_classifier3
This model is a fine-tuned version of ai-forever/ruBert-base on an unknown dataset.
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Trainin... | [
"# HSE_PRAVO_complexity_classifier3\n\nThis model is a fine-tuned version of ai-forever/ruBert-base on an unknown dataset.",
"## Model description\n\nMore information needed",
"## Intended uses & limitations\n\nMore information needed",
"## Training and evaluation data\n\nMore information needed",
"## Train... | [
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"# HSE_PRAVO_complexity_classifier3\n\nThis model is a fine-tuned version of ai-forever/ruBert-base on an unknown dataset.",
"## Model description\n\nMore information needed",
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null | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | twodigit/meta-llama-Meta-Llama-3-8B-Instruct-kocomp_900_llama3_8b-dpo-lora-lr1e-5-e5-b4 | null | [
"transformers",
"safetensors",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T09:07:18+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s)... | [
"TAGS\n#transformers #safetensors #arxiv-1910.09700 #endpoints_compatible #region-us \n",
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Devel... | [
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null | transformers | ## About
<!-- ### quantize_version: 1 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: -->
<!-- ### vocab_type: -->
static quants of https://huggingface.co/NurtureAI/Meta-Llama-3-2x8B-Instruct-MoE-64k-ctx
<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time... | {"language": ["en"], "license": "llama3", "library_name": "transformers", "base_model": "NurtureAI/Meta-Llama-3-2x8B-Instruct-MoE-64k-ctx", "quantized_by": "mradermacher"} | mradermacher/Meta-Llama-3-2x8B-Instruct-MoE-64k-ctx-GGUF | null | [
"transformers",
"gguf",
"en",
"base_model:NurtureAI/Meta-Llama-3-2x8B-Instruct-MoE-64k-ctx",
"license:llama3",
"endpoints_compatible",
"region:us"
] | null | 2024-04-23T09:07:59+00:00 | [] | [
"en"
] | TAGS
#transformers #gguf #en #base_model-NurtureAI/Meta-Llama-3-2x8B-Instruct-MoE-64k-ctx #license-llama3 #endpoints_compatible #region-us
| About
-----
static quants of URL
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
Usage
-----
If you are unsure how to use GGUF file... | [] | [
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] |
text-generation | transformers |
## About Quantization
我们使用modelscope [swift](https://github.com/modelscope/swift/)仓库进行GPTQ量化. 量化文档可以查看[这里](https://github.com/modelscope/swift/blob/main/docs/source/LLM/LLM%E9%87%8F%E5%8C%96%E6%96%87%E6%A1%A3.md). 量化命令如下:
We use the modelscope [swift](https://github.com/modelscope/swift/) repository to perform GPTQ q... | {"language": ["en"], "license": "other", "tags": ["gptq", "int4", "llama3", "facebook", "meta", "pytorch", "llama", "llama-3"], "pipeline_tag": "text-generation", "license_name": "llama3", "license_link": "LICENSE", "extra_gated_prompt": "### META LLAMA 3 COMMUNITY LICENSE AGREEMENT\nMeta Llama 3 Version Release Date: ... | study-hjt/Meta-Llama-3-70B-Instruct-GPTQ-Int4 | null | [
"transformers",
"safetensors",
"llama",
"text-generation",
"gptq",
"int4",
"llama3",
"facebook",
"meta",
"pytorch",
"llama-3",
"en",
"license:other",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"4-bit",
"region:us"
] | null | 2024-04-23T09:08:19+00:00 | [] | [
"en"
] | TAGS
#transformers #safetensors #llama #text-generation #gptq #int4 #llama3 #facebook #meta #pytorch #llama-3 #en #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us
| About Quantization
------------------
我们使用modelscope swift仓库进行GPTQ量化. 量化文档可以查看这里. 量化命令如下:
We use the modelscope swift repository to perform GPTQ quantization. Quantization documentation can be found here. The quantization command is as follows:
Inference:
SFT:
Model Details
-------------
Meta developed and ... | [
"### Use with transformers\n\n\nSee the snippet below for usage with Transformers:",
"### Use with 'llama3'\n\n\nPlease, follow the instructions in the repository.\n\n\nTo download Original checkpoints, see the example command below leveraging 'huggingface-cli':\n\n\nFor Hugging Face support, we recommend using t... | [
"TAGS\n#transformers #safetensors #llama #text-generation #gptq #int4 #llama3 #facebook #meta #pytorch #llama-3 #en #license-other #autotrain_compatible #endpoints_compatible #text-generation-inference #4-bit #region-us \n",
"### Use with transformers\n\n\nSee the snippet below for usage with Transformers:",
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text-generation | transformers |
# Model Card for Model ID
<!-- Provide a quick summary of what the model is/does. -->
## Model Details
### Model Description
<!-- Provide a longer summary of what this model is. -->
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generate... | {"library_name": "transformers", "tags": []} | ohsuz/ohsuz-fin-merges | null | [
"transformers",
"safetensors",
"phi",
"text-generation",
"conversational",
"custom_code",
"arxiv:1910.09700",
"autotrain_compatible",
"endpoints_compatible",
"text-generation-inference",
"region:us"
] | null | 2024-04-23T09:11:21+00:00 | [
"1910.09700"
] | [] | TAGS
#transformers #safetensors #phi #text-generation #conversational #custom_code #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us
|
# Model Card for Model ID
## Model Details
### Model Description
This is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by:
- Funded by [optional]:
- Shared by [optional]:
- Model type:
- Language(s) (NLP):
- License... | [
"# Model Card for Model ID",
"## Model Details",
"### Model Description\n\n\n\nThis is the model card of a transformers model that has been pushed on the Hub. This model card has been automatically generated.\n\n- Developed by: \n- Funded by [optional]: \n- Shared by [optional]: \n- Model type: \n- Language(s)... | [
"TAGS\n#transformers #safetensors #phi #text-generation #conversational #custom_code #arxiv-1910.09700 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us \n",
"# Model Card for Model ID",
"## Model Details",
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