I am really pleased to see 
text
I am really pleased to see 
https://huggingface.co/jpacifico/Chocolatine-2-14B-Instruct-v2.0.3
jpacifico/Chocolatine-2-14B-Instruct-v2.0.3
model
resource
https://huggingface.co/jpacifico/Chocolatine-2-14B-Instruct-v2.0.3
 take #4 on the 14B segment of the Open LLM leaderboard.  It is a fine-tune of a merge of Arcee's 
text
 take #4 on the 14B segment of the Open LLM leaderboard.  It is a fine-tune of a merge of Arcee's 
https://huggingface.co/arcee-ai/Virtuoso-Small-v2
arcee-ai/Virtuoso-Small-v2
model
resource
https://huggingface.co/arcee-ai/Virtuoso-Small-v2
, and my 
text
, and my 
https://huggingface.co/sometimesanotion/Lamarck-14B-v0.7
sometimesanotion/Lamarck-14B-v0.7
model
resource
https://huggingface.co/sometimesanotion/Lamarck-14B-v0.7
 and 
text
 and 
https://huggingface.co/sometimesanotion/Qwenvergence-14B-v12-Prose-DS
sometimesanotion/Qwenvergence-14B-v12-Prose-DS
model
resource
https://huggingface.co/sometimesanotion/Qwenvergence-14B-v12-Prose-DS
.  Don't let the numbers fool you, in its element, it's quite smooth.   I really enjoy merges of Lamarck with near siblings like this one.
text
.  Don't let the numbers fool you, in its element, it's quite smooth.   I really enjoy merges of Lamarck with near siblings like this one.
new_line
new_line
Don't be surprised when it's challenging to bring in the full reasoning strength of a reason-heavy prose model like Qwenvergence v12-DS into a high IFEVAL model like Lamarck or Virtuoso Small v2.  That's a lot of work to get right, because IFEVAL, precise reasoning, and prose quality are often in tension against each other.  Gaining as much as this did is really respectable, and fine-tuning it makes it a more stable base for the coming iterations.
text
Don't be surprised when it's challenging to bring in the full reasoning strength of a reason-heavy prose model like Qwenvergence v12-DS into a high IFEVAL model like Lamarck or Virtuoso Small v2.  That's a lot of work to get right, because IFEVAL, precise reasoning, and prose quality are often in tension against each other.  Gaining as much as this did is really respectable, and fine-tuning it makes it a more stable base for the coming iterations.
I am really pleased to see https://huggingface.co/jpacifico/Chocolatine-2-14B-Instruct-v2.0.3 take #4 on the 14B segment of the Open LLM leaderboard.  It is a fine-tune of a merge of Arcee's https://huggingface.co/arcee-ai/Virtuoso-Small-v2, and my https://huggingface.co/sometimesanotion/Lamarck-14B-v0.7 and https://huggingface.co/sometimesanotion/Qwenvergence-14B-v12-Prose-DS.  Don't let the numbers fool you, in its element, it's quite smooth.   I really enjoy merges of Lamarck with near siblings like this one.

Don't be surprised when it's challenging to bring in the full reasoning strength of a reason-heavy prose model like Qwenvergence v12-DS into a high IFEVAL model like Lamarck or Virtuoso Small v2.  That's a lot of work to get right, because IFEVAL, precise reasoning, and prose quality are often in tension against each other.  Gaining as much as this did is really respectable, and fine-tuning it makes it a more stable base for the coming iterations.
👍
John6666 jpacifico gn00029914 dantezxcd
665fef5a4794222f6a2fe605
https://cdn-avatars.huggingface.co/v1/production/uploads/665fef5a4794222f6a2fe605/sUF9NsMRNxdiEYKJbIbCk.jpeg
sometimesanotion
sometimesanotion
user